Management device, management method, computer program, and management system

Abstract

To efficiently collect performance data on an agricultural machine that can change operation modes.SOLUTION: A device according to one aspect of the present invention is a management device that communicates with an agricultural machine whose operation modes include an automatic operation and a non-automatic operation, and includes a processing device for creating an automatic operation plan for the agricultural machine, a communication device for transmitting the automatic operation plan to the agricultural machine, and receiving performance data that the agricultural machine collects on it, and a storage device for storing the received performance data. The performance data includes data that the agricultural machine has collected during the non-automatic operation performed by the intervention that has occurred during the automatic operation according to the automatic operation plan.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to a management device, a management method, a computer program, and a management system for agricultural machinery.

Background Art

[0002] Patent Document 1 describes a work vehicle support system including a detection module that detects the position of the vehicle itself, and an outer shape map calculation unit that calculates an outer shape map of an unworked area within a work planned area from the vehicle position data acquired by the detection module when traveling around the outer periphery of the work planned area. Patent Document 2 describes an automatic driving system that can ensure sufficient safety with a reasonable configuration when moving a work vehicle between fields by automatic driving.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] In promoting the automation of agricultural machinery, it is desirable to integrally manage the performance data in the case of automatic driving and the performance data in the case of non-automatic driving. However, Patent Documents 1 and 2 do not assume an efficient method for collecting the performance data during automatic driving and the performance data during non-automatic driving. An object of the present disclosure is to provide a technique capable of efficiently collecting the performance data of agricultural machinery whose driving mode can be changed.

Means for Solving the Problems

[0005] An apparatus according to one aspect of the present disclosure is a management apparatus for communicating with an agricultural machine whose operating modes include automated driving and non-autonomous driving, comprising: a processing device for creating an automated driving plan for the agricultural machine; a communication device for transmitting the automated driving plan to the agricultural machine and receiving performance data of the agricultural machine collected by the agricultural machine; and a storage device for storing the received performance data, wherein the performance data includes data collected by the agricultural machine during non-autonomous driving performed by interventions occurring during automated driving in accordance with the automated driving plan.

[0006] A method relating to one aspect of the present disclosure is a method for managing agricultural machinery, performed by a management device that communicates with agricultural machinery whose operating modes include automated driving and non-autonomous driving, comprising the steps of: creating an automated driving plan for the agricultural machinery; transmitting the automated driving plan to the agricultural machinery; receiving performance data of the agricultural machinery collected by the agricultural machinery; and storing the received performance data, wherein the performance data includes data collected by the agricultural machinery during non-autonomous driving performed by interventions occurring during automated driving in accordance with the automated driving plan.

[0007] A computer program according to one aspect of the present disclosure is a computer program for operating a computer as a management device that communicates with an agricultural machine whose operating modes include automatic driving and non-automatic driving, the program comprising the steps of creating an automatic driving plan for the agricultural machine, transmitting the automatic driving plan to the agricultural machine, receiving performance data of the agricultural machine collected by the agricultural machine, and storing the received performance data, the performance data including data collected by the agricultural machine during non-automatic driving performed by interventions occurring during automatic driving in accordance with the automatic driving plan.

[0008] A system according to one aspect of the present disclosure is a management system for agricultural machinery, comprising: an agricultural machine whose operating modes include automatic operation and manual operation; and a management device that communicates with the agricultural machine, wherein the management device transmits an automatic operation plan for the agricultural machine to the agricultural machine; the agricultural machine transmits performance data of itself collected during manual operation to the management device if there is an intervention to manual operation during automatic operation in accordance with the automatic operation plan; and the management device stores the received performance data of manual operation in its own storage device.

[0009] Embodiments of the present disclosure may be implemented by apparatus, systems, methods, integrated circuits, computer programs, or computer-readable non-temporary storage media, or any combination thereof. Computer-readable storage media may include either volatile or non-volatile storage media. Apparatus may consist of a plurality of separate devices. If consisting of a plurality of separate devices, they may be arranged in a single housing or in two or more separate housings. [Effects of the Invention]

[0010] According to this disclosure, it is possible to efficiently collect performance data for agricultural machinery whose operating modes can be changed. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 is a schematic diagram showing an example of the overall configuration of a work support system. [Figure 2] Figure 2 is a side view showing an example of the structure of a work vehicle and implement. [Figure 3] Figure 3 is a block diagram showing an example of the configuration of an in-vehicle communication system for a work vehicle. [Figure 4] Figure 4 is a perspective view showing an example of an operating terminal and a group of operating switches. [Figure 5] Figure 5 is a block diagram showing an example of the internal configuration of a management device, a management terminal, and a remote terminal. [Figure 6]FIG. 6 is an explanatory diagram showing an example of a setting screen and information processing of information necessary for creating an automatic driving plan. [Figure 7] FIG. 7 is a diagram showing an example of a work cost table. [Figure 8] FIG. 8 is a diagram showing an example of an agricultural machine current situation table. [Figure 9] FIG. 9 is a diagram showing an example of a remaining task table. [Figure 10] FIG. 10 is a diagram showing an example of an automatic driving plan for one agricultural machine. [Figure 11] FIG. 11 is a state transition diagram showing an example of operation mode switching processing. [Figure 12] FIG. 12 is a sequence diagram showing an example of a plan change communication sequence. [Figure 13] FIG. 13 is an explanatory diagram showing an example of a change in field work accompanying a plan change. [Figure 14] FIG. 14 is a flowchart showing an example of data storage and update executed by a management device. [Figure 15] FIG. 15 is an explanatory diagram showing an example of a work change after remote operation intervention. [Figure 16] FIG. 16 is an explanatory diagram showing an example of an update of an agricultural machine current situation table. [Figure 17] FIG. 17 is an explanatory diagram showing an example of an update of a remaining task table. [Figure 18] FIG. 18 is an explanatory diagram showing an example of an automatic driving plan created by recalculation. [Figure 19] FIG. 19 is a diagram showing an example of movement trajectory data. [Figure 20] FIG. 20 is a diagram showing an example of work achievement data.

MODE FOR CARRYING OUT THE INVENTION

[0012] <SUMMARY OF THE EMBODIMENTS OF THE PRESENT DISCLOSURE> Hereinafter, the summary of the embodiments of the present disclosure will be listed and described. (1) The apparatus according to this embodiment is a management apparatus that communicates with an agricultural machine whose operating modes include automatic operation and non-automatic operation, and comprises a processing device that creates an automatic operation plan for the agricultural machine, a communication device that transmits the automatic operation plan to the agricultural machine and receives performance data of the machine collected by the agricultural machine, and a storage device that stores the received performance data, wherein the performance data includes data collected by the agricultural machine during non-automatic operation performed by interventions that occur during automatic operation in accordance with the automatic operation plan.

[0013] According to the management device of this embodiment, the performance data stored in the storage device of the management device includes data collected by the agricultural machine during non-autonomous operation, which is performed as a result of interventions that occur during autonomous operation according to the autonomous operation plan. Therefore, both performance data during autonomous operation and performance data during non-autonomous operation can be collected from a single agricultural machine. Accordingly, performance data for agricultural machines whose operating mode can be changed can be collected efficiently.

[0014] (2) In the management device of this embodiment, the performance data may further include data collected by the agricultural machine during the modified automated operation that is carried out in response to a change request that occurred during the automated operation in accordance with the automated operation plan. In this way, it is possible to collect even more performance data from the modified automated operation of a single agricultural machine, thus enabling more efficient collection of performance data for agricultural machines.

[0015] (3) In the management device of this embodiment, the non-automatic operation may include at least one of manual operation, in which a human directly operates the agricultural machine, and remote operation, in which the agricultural machine is remotely operated using an operating terminal. In this case, in addition to performance data from automated operation, it becomes possible to collect at least one of the following from a single agricultural machine: performance data from manual operation and performance data from remote operation.

[0016] (4) In the management device of this embodiment, the storage device may have a database in which the performance data is stored so as to be able to identify which of the following periods was collected: the period of automated driving according to the automated driving plan, the period of manual driving, the period of remote driving, and the period of modified automated driving. This approach allows the collected performance data to be identified by operating mode, making it easier to conduct analyses or studies, such as determining which operating mode was optimal for a given task.

[0017] (5) In the control device of this embodiment, the intervention in manual operation may be conditional on the detection of direct human operation. The reason is that in manual operation, it is assumed that a human will properly operate the work vehicle, so there is no particular problem in suddenly switching to manual operation triggered solely by the detection of direct operation.

[0018] (6) In the management device of this embodiment, the release of the intervention in manual operation may be conditional on the direct operation being undetected for a predetermined period of time, the automatic operation being possible, and the operation of the agricultural machinery being stopped. In this case, since the conditions for releasing manual driving intervention include stopping the operation of the agricultural machinery, a smoother transition from manual to automatic driving is achieved compared to releasing manual driving and switching to automatic driving while driving.

[0019] (7) In the management device of this embodiment, the intervention of remote operation may be conditional on the receipt of a remote start request, the stabilization of the communication status, and the cessation of the operation of the agricultural machinery. The reason is that, unlike manual operation, remote operation may involve a delay between the time the control terminal is operated and the actual start of operation by the agricultural machinery. Therefore, stable communication and the cessation of agricultural machinery operation should be included as conditions for intervention.

[0020] (8) In the management device of this embodiment, the release of the intervention in the remote operation may be conditional on the receipt of a remote termination request, the state in which automatic operation is possible, and the stopping of the operation of the agricultural machinery. In this case, since the conditions for deactivating remote control intervention include stopping the operation of the agricultural machinery, a smoother transition from remote control to autonomous driving is achieved compared to deactivating remote control and switching to autonomous driving while driving.

[0021] (9) In the management device of this embodiment, the storage device further stores planning data necessary for creating the automated driving plan, and the processing device may use the updated planning data to create the automated driving plan to be created in the future if it updates the planning data after the intervention or change request. In this way, the automated driving plan is created using the updated and correct planning data, thus preventing the creation of incorrect automated driving plans.

[0022] (10) In the management device of this embodiment, the planning data includes static data whose content does not change even when the operating mode changes, and dynamic data whose content may change when the operating mode changes, and the processing device may make the dynamic data the target of update when there is an intervention or change request. The reason is that static data, whose content does not change even when the driving mode changes, does not need to be updated.

[0023] (11) In the management device of this embodiment, the static data may include at least one of the following: farm equipment data, farm utilization plan, and farm machinery information. The reason is that this data is configuration information set by the user of the management device, and therefore is not affected by changes in the operating mode.

[0024] (12) In the management device of this embodiment, the dynamic data may include at least one of the following: data representing the current status of the agricultural machinery and data representing the progress of the tasks constituting the automated driving plan. The reason is that the current status of agricultural machinery and the progress of tasks change when the travel route and the order of operations change, so the data content can change when the operating mode changes.

[0025] (13) The method according to this embodiment is a management method that is performed in the management device described in (1) to (12) above. Therefore, the management method according to this embodiment has the same effects as the management device described in (1) to (12) above.

[0026] (14) The computer program according to this embodiment is a computer program that causes the computer to function as the management device described in (1) to (12) above. Therefore, the computer program according to this embodiment has the same effects as the management devices described in (1) to (12) above.

[0027] (15) The management system of this embodiment is a management system for agricultural machinery comprising an agricultural machine whose operating modes include automatic operation and manual operation, and a management device that communicates with the agricultural machine, wherein the management device transmits an automatic operation plan for the agricultural machine to the agricultural machine, and when the agricultural machine intervenes in manual operation during automatic operation in accordance with the automatic operation plan, it transmits performance data of the machine collected during the manual operation to the management device, and the management device stores the received performance data during manual operation in its storage device.

[0028] According to the management system of this embodiment, if an agricultural machine whose operating modes include automatic and non-automatic operation intervenes in manual operation during automatic operation according to the automatic operation plan, it transmits the machine's performance data collected during the manual operation to the management device, and the management device stores the received performance data from the manual operation in its own memory device. Thus, both performance data from automatic operation and performance data from manual operation can be collected from a single agricultural machine. Therefore, performance data from agricultural machines whose operating modes can be changed can be collected efficiently.

[0029] (16) In the management system of this embodiment, the operating mode further includes remote operation, the management system further includes a remote terminal that communicates with the agricultural machine and causes the agricultural machine to perform remote operation, the agricultural machine transmits the performance data of the machine collected during the remote operation to the management device when remote operation intervention occurs during automatic operation in accordance with the automatic operation plan, and the management device may store the received performance data during remote operation in its own storage device.

[0030] In this way, performance data from remote operation can be collected from a single agricultural machine, making it possible to collect performance data for agricultural machines more efficiently.

[0031] (17) In the management system of this embodiment, the remote terminal can transmit a request to change the automatic operation to the agricultural machine, the agricultural machine transmits the performance data of the machine collected during the modified automatic operation performed in accordance with the change request received during automatic operation in accordance with the automatic operation plan to the management device, and the management device may store the performance data of the modified automatic operation that it has received in its storage device.

[0032] In this way, it is possible to collect even more performance data from the modified automated operation of a single agricultural machine, thus enabling more efficient collection of performance data for agricultural machines.

[0033] <Details of the embodiments of this disclosure> The embodiments of the present invention will be described in detail below with reference to the drawings. At least some of the embodiments described below may be combined in any way.

[0034] [Definition of Terms] Before describing the details of this embodiment, we will first define the terms used in this specification. "Agricultural work" refers to the work performed by agricultural machinery on the ground in a field. It is also called "ground work" or simply "work." Agricultural work includes, for example, tilling, sowing, pest control, fertilizing, planting crops, and harvesting.

[0035] "Agricultural machinery" refers to machines used for agricultural purposes and is sometimes abbreviated as "farm equipment." Examples of agricultural machinery include tractors, harvesters, rice transplanters, riding cultivators, vegetable transplanters, lawnmowers, seeders, fertilizer spreaders, and agricultural mobile robots. In the case of tractors, the work vehicle may function as an agricultural machine on its own, or the work implements attached to the work vehicle and the entire work vehicle may function as a single agricultural machine.

[0036] "Work vehicles": These are vehicles that can perform agricultural work in fields. "Work equipment": This refers to equipment that can be detachably attached to a work vehicle and used to perform agricultural work while being towed by the work vehicle. It is also called "implement."

[0037] "Working mode": This refers to agricultural machinery moving while performing work. Working mode can be performed regardless of the operating mode. "Inter-field movement" refers to agricultural machinery moving along public roads or farm roads between fields without performing any work. Inter-field movement can be performed regardless of the operating mode. Inter-field movement may include barns or warehouses as the starting point, intermediate point, or destination.

[0038] "Operating Mode": When the operating method of agricultural machinery can be switched according to the user's preferences, the individual operating methods that can be selected for the agricultural machinery are called operating modes. The operating modes that agricultural machinery can perform vary depending on the model or type of the machinery, but may include manual operation, remote operation, and automatic operation, as described below.

[0039] "Manual operation": This refers to operation in which a person directly operates agricultural machinery. It also includes cases where a person riding in a work vehicle operates the implement. "Manual Driving" and "Manual Steering": Manual driving refers to agricultural machinery being driven by manual operation, and manual steering refers to agricultural machinery being steered by manual operation. Both manual driving and manual steering are included in the concept of manual driving.

[0040] "Autonomous driving": This refers to the operation of agricultural machinery by a control system that operates the machinery. In autonomous driving, the control system performs functions such as starting and stopping the vehicle, automatic steering, and speed adjustment. In work vehicles, it may also control the raising and lowering of implements and the start and stop of operations. "Automatic Driving" and "Automatic Steering": Automatic driving refers to agricultural machinery being driven automatically, and automatic steering refers to agricultural machinery being steered automatically. Automatic driving and automatic steering are included in the concept of autonomous driving.

[0041] "Remote operation" refers to the operation of agricultural machinery by a person located at a distance from the machinery using an operating terminal (remote controller). Remote operation also includes a person at a distance remotely operating implements attached to a work vehicle. "Remote driving" and "remote steering": Remote driving refers to agricultural machinery being driven by remote control, and remote steering refers to agricultural machinery being steered by remote control. Remote driving and remote steering are included in the concept of remote driving. "Non-automated driving": This refers to driving modes that are not automated. In this embodiment, manual driving and remote driving fall under the category of non-automated driving.

[0042] "Target path": This is the path that the agricultural machine should take during autonomous driving. The target path may be generated by either the agricultural machine's control unit or an external device that communicates with the agricultural machine. The target path generated by the external device is transmitted to the agricultural machine by that external device. The control unit for agricultural machinery controls the drive system of the agricultural machinery so that it moves along a target path. This allows the control unit to move the agricultural machinery toward a destination such as a field, barn, or implement storage area.

[0043] "Performance Data": This data represents the operational performance of agricultural machinery. Performance data is collected by the agricultural machinery's control unit and reported to the management unit. Specifically, the agricultural machinery's control unit transmits its own performance data to the management unit in real time or at predetermined intervals. The management device stores performance data received from the managed agricultural machinery, categorized by the identification information of each agricultural machine. The content of the performance data varies depending on the work performed, but it can be broadly categorized into, for example, "movement trajectory data," "work performance data," "control performance data," and "autonomous driving data."

[0044] "Movement trajectory data": This is time-series data of the location (current position) of agricultural machinery. "Work Performance Data": This is time-series data on agricultural work performed by agricultural machinery (e.g., fertilizer application amount, PTO rotation speed, etc.). "Control Performance Data": This refers to time-series data of various sensor data and / or control information for actuators possessed by agricultural machinery. "Autonomous driving data": This refers to time-series data of control information related to autonomous driving, output by the control device of agricultural machinery during autonomous driving.

[0045] "Automated Driving Plan": This is information that defines the future tasks to be performed by agricultural machinery through autonomous driving. The automated driving plan may consist of, for example, the content of the tasks, which are the units of work that the agricultural machinery will perform through autonomous driving, the execution time of the tasks (year, month, day and time), and task identification information (hereinafter also referred to as "Task ID"). The tasks may include not only the work performed in the field, but also the routes taken by agricultural machinery when moving between fields (also called "inter-field routes").

[0046] "Planning data": This is data used for creating or updating autonomous driving plans. Planning data can be broadly categorized into, for example, "static data" and "dynamic data." "Static data": This is planning data whose content does not change even if the operating mode of agricultural machinery changes. Static data includes, for example, "equipment data," "utilization plan," "agricultural machinery information," and "work cost data" set by farm managers.

[0047] "Equipment data": This refers to information representing the location of real estate facilities included in the farm, such as fields, barns, and warehouses. The location information of a field may consist not only of points such as the center or corners of the field, but also of a set of coordinates of a predetermined granularity that can identify the boundaries of the field. "Land Use Plan": This is information representing the land use plan for a given period (e.g., one year). The land use plan may consist of, for example, the land use period for each field and the types of crops to be cultivated during that period.

[0048] "Agricultural Machinery Information": This information represents the type of one or more agricultural machines (movable property) that can be used on a farm. The type of agricultural machinery is defined, for example, by product number or model number. In the case of work vehicles, it also includes the types of implements that can be mounted on the work vehicle and are actually usable. "Work Cost Data": This data defines the cost (e.g., time required) of each task that can be performed on the farm. Work cost data may consist of the work content and time required for each task's identification information (hereinafter also referred to as "task ID"). The time required may be defined manually or calculated by a management system from equipment data and agricultural machinery information.

[0049] "Dynamic data": This is planning data whose content may change when the operating mode of agricultural machinery changes. Dynamic data includes "current agricultural machinery data" and "remaining tasks data," among others. "Agricultural Machinery Status Data": This data represents the current status of each agricultural machine included in the agricultural machinery information. Examples of current status data may include the machine's current location, current operating mode, and the type of implements currently installed (in the case of a tractor).

[0050] "Remaining Task Data": This data represents the progress of tasks that make up the autonomous driving plan. Remaining task data may consist of, for example, a task ID, a work ID corresponding to the task ID, a status to identify whether the task is completed or not, and the period during which the task should be performed.

[0051] [Overall System Configuration] Figure 1 is a schematic diagram showing an example of the overall configuration of an agricultural machinery management system. As shown in Figure 1, the management system 900 of this embodiment includes a work vehicle 100, a first terminal device 400, a second terminal device 500, and a management device 600. Although Figure 1 shows one work vehicle 100, the management system 900 may include one or more other work vehicles 100, or other types of agricultural machinery.

[0052] The operating modes of the work vehicle 100 include at least three types: manual operation, remote operation, and automatic operation. In automatic operation mode, the work vehicle 100 moves autonomously using a control device (for example, the electronic control unit 180 in Figure 3). The control device for the work vehicle 100 is installed inside the work vehicle 100 and is capable of controlling the speed and steering of the work vehicle 100.

[0053] Therefore, the work vehicle 100 in autonomous driving mode can operate unmanned and perform work and travel both inside and outside the field (including roads). In the case of remote operation, the work vehicle 100 performs work driving or inter-field movement in response to remote operation by the user 510 of the second terminal device 500. The interface of the operating device 540 connected to the remote terminal 500 is configured so that remote operation by the user 510 is almost the same as manual operation from the driver's seat.

[0054] The management device 600 is a server computer managed by, for example, a business operator that operates the management system 900 (for example, an agricultural machinery manufacturer or an information technology company). Hereinafter, the management device 600 will be referred to as the "management server 600". The management server 600 centrally manages data related to agricultural machinery and provides support for farm work using this data. The management server 600 can create an automated driving plan to be executed by agricultural machinery such as the work vehicle 100 using information received from the first terminal device 400.

[0055] The first terminal device 400 is a computer used by a user (hereinafter referred to as the "management user") 410 who remotely manages the work vehicle 100. Hereinafter, the first terminal device 400 will be referred to as the "management terminal 400". The management user 410 is, for example, a farm manager. The management terminal 400 is, for example, a stationary computer such as a desktop PC. The management terminal 400 may also be a mobile device such as a smartphone, tablet computer, or laptop computer.

[0056] The management terminal 400 can display a screen on its display that shows the settings for the information necessary to create an automated driving plan. When the management user 410 enters the necessary information on the settings screen and performs the submit operation, the management terminal 400 sends the entered information to the management server 600. The management terminal 400 can also be used to monitor the work vehicle 100. For example, the management terminal 400 displays video footage captured by the work vehicle 100's camera on its display. The management user 410 can then check the surroundings of the work vehicle 100 based on the displayed video footage.

[0057] The second terminal device 500 is a computer used by the user 510 who remotely operates the work vehicle 100 (hereinafter referred to as the "operating user"). Hereinafter, the second terminal device 500 will be referred to as the "remote terminal 500". The remote terminal 500 is, for example, a stationary computer such as a desktop PC. The remote terminal 500 is equipped with an operating device 540 that enables the operating user 510 to perform operations almost equivalent to those performed by the occupant of the work vehicle 100. The operating device 540 may also include the operating terminal 200 and the group of operating switches 210 (see Figure 4) of the work vehicle 100.

[0058] In Figure 1, the management terminal 400 and the remote terminal 500 are located in different places, but they may be located in the same room within the same building. In this case, the management user 410 and the operating user 510 may be the same person. In Figure 1, the management terminal 400 and the remote terminal 500 are separate computers, but the management terminal 400 and the remote terminal 500 may be a single computer capable of comprehensively performing their respective functions.

[0059] [Examples of work vehicle structures] Figure 2 is a side view showing an example of the structure of the work vehicle 100 and implement 300. As shown in Figure 2, the work vehicle 100 comprises a vehicle body 101, a prime mover (engine) 102, and a transmission 103. The vehicle body 101 comprises tires (wheels) 104 and a cabin 105. The tires 104 include a pair of front wheels 104F and a pair of rear wheels 104R. One or both of the front wheels 104F and the rear wheels 104R may be crawlers.

[0060] The cabin 105 is equipped with a steering device 106, a driver's seat 107, an operating terminal 200 (see Figure 4), and a group of operating switches 210 (see Figure 4). The work vehicle 100 is equipped with multiple cameras 120. The cameras 120 are installed, for example, at various locations on the front, rear, left, and right sides of the work vehicle 100. The cameras 120 capture images of the environment surrounding the work vehicle 100 and generate image data.

[0061] The image data generated by camera 120 is transmitted to the management terminal 400 and the remote terminal 500, respectively. Image data is used, for example, by users 410 and 510 to monitor or operate the work vehicle 100 during unmanned operation. Image data is also used as source data for image recognition of road markings, signs, displays, or surrounding obstacles.

[0062] The work vehicle 100 is equipped with a positioning device 110, including a GNSS receiver, on top of, for example, the cabin 105. The GNSS receiver includes an antenna for receiving GNSS satellite signals and a processor for calculating the position of the work vehicle 100 based on the received signals. GNSS is a general term for satellite positioning systems such as GPS (Global Positioning System), QZSS (Quasi-Zenith Satellite System: e.g., "Michibiki"), GLONASS (Russia), Galileo (Europe), and BeiDou (China).

[0063] The positioning device 110 is equipped with an inertial measuring unit (IMU). The IMU measures the tilt and minute movements of the work vehicle 100. By using the IMU's measurement data to supplement position data based on satellite signals, positioning accuracy can be improved.

[0064] The work vehicle 100 is equipped with a LiDAR sensor 140. The LiDAR sensor 140 is installed, for example, on the lower front of the vehicle body 101. The LiDAR sensor 140 may be installed in other locations. The LiDAR sensor 140 repeatedly outputs sensor data indicating the distance and direction of each measurement point on objects in the surrounding environment, or the two-dimensional or three-dimensional coordinate values ​​of each measurement point, while the work vehicle 100 is in motion.

[0065] The sensor data output from the LiDAR sensor 140 is processed by the control device of the work vehicle 100. The control device of the work vehicle 100 can perform tasks such as generating environmental maps based on sensor data using algorithms such as SLAM (Simultaneous Localization and Mapping). Sensor data from the LiDAR sensor 140 is also used for obstacle detection.

[0066] The positioning device 110 may also use data acquired by the camera 120 or the LiDAR sensor 140 for positioning. If there are landmarks around the work vehicle 100, the position of the work vehicle 100 can be estimated with high accuracy based on the data acquired by the camera 120 or LiDAR sensor 140 and the environmental map recorded in the storage device.

[0067] The work vehicle 100 is equipped with multiple obstacle sensors 130. The obstacle sensors 130 are sensors for detecting obstacles in the surroundings during autonomous driving, and in the example shown in Figure 2, obstacle sensors 130 are installed in front of and behind the cabin 105. The obstacle sensor 130 may also be placed in other locations. For example, one or more obstacle sensors 130 may be provided at any location on the side, front, and rear of the vehicle body 101.

[0068] The prime mover 102 is, for example, a diesel engine. Alternatively, an electric motor may be used as the prime mover 102, either in place of or in addition to the diesel engine. The transmission 103 is a transmission that changes the propulsion force and travel speed of the work vehicle 100 by switching between gears. The transmission 103 can also switch the work vehicle 100 between forward and reverse.

[0069] The steering system 106 includes a steering wheel, a steering shaft, and a power steering system that assists steering by the occupant. When the front wheels 104F are steering wheels, the steering angle (also referred to as the "steering angle") of the front wheels 104F changes in accordance with the rotation of the steering wheel, and the direction of travel of the work vehicle 100 changes. The power steering system includes a hydraulic system or electric motor that generates assist force, and in the case of automatic steering, the steering angle is automatically adjusted by the hydraulic system or electric motor.

[0070] A coupling device 108 is provided at the rear of the vehicle body 101. The coupling device 108 includes a three-point support device (also called a "three-point link" or "three-point hitch"), a PTO (Power Take-Off) shaft, a universal joint, and a communication cable. The implement 300 can be attached to and detached from the coupling device 108. The coupling device 108 raises and lowers the three-point linkage, for example, by a hydraulic system, thereby changing the position or orientation of the implement 300. Power may also be transmitted to the implement 300 by a universal joint.

[0071] The work vehicle 100 tows the implement 300, causing the implement 300 to perform a predetermined task. The coupling device 108 may be positioned in front of the vehicle body 101. In this case, the implement is connected to the front of the work vehicle 100. In Figure 2, a rotary tiller is shown as an example of implement 300. Implement 300 is not limited to tillers; it may also be a jeep (seeder), spreader (fertilizer applicator), transplanter, mower (grass cutter), rake, baler (grass collector), harvester (harvesting machine), sprayer, or harrow.

[0072] [In-vehicle communication system for work vehicles] Figure 3 is a block diagram showing an example of the configuration of the in-vehicle communication system of the work vehicle 100. As shown in Figure 3, the work vehicle 100 communicates with the implement 300 via a communication cable (dashed arrow) included in the coupling device 108. The work vehicle 100 can also communicate with the management terminal 400, the remote terminal 500, and the management server 600 via the network 800.

[0073] The work vehicle 100 is equipped with a positioning device 110, a camera 120, an obstacle sensor 130, a LiDAR sensor 140, a group of sensors 150 for detecting the operating status of the vehicle, a control system 160, and a communication device 190. These components are connected via a bus for communication. The work vehicle 100 further includes an operating terminal 200, a group of operating switches 210, a buzzer 220, a status detection device 230, and a drive device 240. These components are also connected via a bus for communication.

[0074] The positioning device 110 includes a GNSS receiver 111, an RTK receiver 112, an inertial measurement unit (IMU) 115, and a processing circuit 116. The sensor group 150 includes a wheel sensor 152, a steering angle sensor 154, and an axle sensor 156. The control system 160 includes a storage device 170 and a control device 180. The control device 180 includes a plurality of electronic control units (ECUs) 181 to 186. The implement 300 comprises a drive device 340, a control device 380, and a communication device 390.

[0075] The GNSS receiver 111 of the positioning device 110 receives satellite signals transmitted from multiple GNSS satellites and generates GNSS data based on the satellite signals. GNSS data is generated in a predetermined format, such as NMEA0183, and includes values ​​indicating the satellite identification number, elevation angle, azimuth angle, and received signal strength. The positioning device 110 performs positioning using, for example, RTK (Real-Time Kinematic)-GNSS.

[0076] In RTK-GNSS, in addition to satellite signals from GNSS satellites, correction signals transmitted by a reference station (not shown) are used. The reference station is installed near the field where the work vehicle 100 is traveling (for example, within 1 km of the work vehicle 100). The reference station generates a correction signal, for example in RTCM format, based on satellite signals from multiple GNSS satellites and transmits it to the positioning device 110.

[0077] The RTK receiver 112 includes an antenna and a modem and receives a correction signal from a base station. The processing circuit 116 corrects the positioning result from the GNSS receiver 111 using the correction signal. By employing RTK-GNSS, positioning with an accuracy of within a few centimeters of error becomes possible. The position information obtained from the positioning results includes numerical data of latitude, longitude, and altitude, and is generated by positioning using RTK-GNSS. The positioning device 110 calculates the position of the work vehicle 100 at a frequency of, for example, 1 to 10 times per second.

[0078] In addition to RTK-GNSS, positioning methods that can obtain relatively high-precision location information (such as interferometric positioning or relative positioning) may also be used. For example, the positioning device 110 may perform positioning using VRS (Virtual Reference Station) or DGPS (Deferential Global Positioning System). If the required positional accuracy can be ensured without a correction signal from a reference station, positional information may be generated without using a correction signal. In this case, the positioning device 110 does not need to be equipped with an RTK receiver 112.

[0079] The IMU115 includes a 3-axis accelerometer and a 3-axis gyroscope. The IMU115 may also include an orientation sensor such as a 3-axis geomagnetic sensor. The IMU115 outputs signals indicating parameters such as acceleration, velocity, displacement, and attitude of the work vehicle 100. The processing circuit 116 can estimate the position and orientation of the work vehicle 100 with higher accuracy by using not only satellite signals and correction signals, but also the output signals of the IMU 115. Thus, the output signals of the IMU 115 are used to correct or supplement the position of the work vehicle 100.

[0080] Therefore, in the example shown in Figure 3, the processing circuit 116 can calculate the position of the work vehicle 100 based on the output signals of the GNSS receiver 111, the RTK receiver 112, and the IMU 115. The processing circuit 116 may further estimate or correct the position of the work vehicle 100 based on the data acquired by the camera 120 or LiDAR sensor 140. By utilizing the data acquired by the camera 120 or LiDAR sensor 140, the accuracy of positioning can be further improved.

[0081] Camera 120 is an imaging device that captures the environment around the work vehicle 100. Camera 120 comprises an image sensor such as a CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor), an optical system including one or more lenses, and a signal processing circuit. The camera 120 captures images of the environment surrounding the work vehicle 100 while the vehicle is in motion and generates image (e.g., video) data.

[0082] Camera 120 captures video at a frame rate of, for example, 3 fps (frames per second) or higher. The image data generated by camera 120 is transmitted to the management terminal 400 or the remote terminal 510. Therefore, the management user 410 or the operating user 510 can check the environment around the work vehicle 100. The image data generated by the camera 120 may be used for positioning or obstacle detection.

[0083] The work vehicle 100 illustrated in Figure 2 is equipped with multiple cameras 120 at different locations on the work vehicle 100, but it may also be equipped with only a single camera. A visible light camera that generates visible light images and an infrared camera that generates infrared images may be provided separately. Both the visible light camera and the infrared camera may be provided as cameras that generate surveillance images. The infrared camera can also be used for detecting obstacles at night.

[0084] The obstacle sensor 130 detects objects present around the work vehicle 100. The obstacle sensor 130 includes, for example, a laser scanner or an ultrasonic sonar. The obstacle sensor 130 outputs a signal indicating the presence of an object relatively close to itself. Multiple obstacle sensors 130 may be installed at different locations on the work vehicle 100. For example, multiple laser scanners and multiple ultrasonic sonars may be placed at different locations. This reduces blind spots around the work vehicle 100.

[0085] The wheel sensor 152 measures the rotation angle of the steering wheel of the work vehicle 100, and the steering angle sensor 154 measures the steering angle of the steering wheel (front wheel 104F). The values ​​measured by the wheel sensor 152 and the steering angle sensor 154 are used for steering control by the control device 180.

[0086] The axle sensor 156 measures the rotational speed of the axle to which the tire 104 is connected, that is, the number of rotations per unit time. The axle sensor 156 may employ, for example, a magnetoresistive element (MR), a Hall element, or a sensor utilizing an electromagnetic pickup. The axle sensor 156 outputs a numerical value indicating, for example, the number of rotations per minute (in rpm). The axle sensor 156 is used to measure the speed of the work vehicle 100.

[0087] The drive system 240 includes various devices necessary for the movement of the work vehicle 100 and the drive of the implement 300, such as the prime mover 102, the transmission 103, the steering system 106, and the coupling device 108. The prime mover 102 is an internal combustion engine, such as a diesel engine. The drive unit 240 may be equipped with an electric motor for traction, either in place of or in conjunction with an internal combustion engine.

[0088] The buzzer 220 is an audio output device that emits a warning sound to indicate an abnormality. The audio output device may also be a speaker. The buzzer 220 emits a warning sound, for example, when an obstacle is detected during autonomous driving. The buzzer 220 is controlled by the control device 180.

[0089] The condition detection device 230 is a device equipped with one or more sensors for detecting the mounting status of the implement 300, deterioration of the implement 300, deterioration of parts of the work vehicle 100, or shortage of materials. One or more sensors may include, for example, an image sensor positioned to capture images of the implement 300, parts of the work vehicle 100, or materials consumed in agricultural work, and at least one of a sensor for measuring the remaining amount of materials.

[0090] The storage device 170 includes one or more storage media such as flash memory or magnetic disks. The storage device 170 stores various data generated by the positioning device 110, camera 120, obstacle sensor 130, sensor group 150, state detection device 230, and control device 180. The data stored in the storage device 170 includes an environmental map, which is map data of the environment in which the work vehicle 100 travels, and data of the target route in autonomous driving.

[0091] The environmental map includes information on multiple fields where the work vehicle 100 performs agricultural work and the surrounding roads. The environmental map and target route may be generated by the control device 180 itself, or by the processor 660 of the management server 600. The storage device 170 also stores the automated driving plan (hereinafter sometimes simply referred to as "plan") received by the communication device 190 from the management server 600 or the like.

[0092] The automated driving plan may include information indicating multiple farming tasks that the work vehicle 100 will perform over multiple working days. The storage device 170 also stores computer programs that cause each ECU of the control device 180 to perform various operations. Such computer programs may be provided to the work vehicle 100 via a storage medium (e.g., semiconductor memory or optical disc) or a telecommunications line (e.g., the Internet).

[0093] The control device 180 is composed of a group of ECUs, including, for example, the following multiple ECUs. 1) ECU181 for speed control 2) ECU182 for steering control 3) ECU183 for implement control 4) ECU184 for automatic driving control 5) ECU185 for route creation 6) ECU186 for state estimation

[0094] The ECU 181 controls the prime mover 102, the transmission 103, and the brakes included in the drive unit 240. This adjusts the speed of the work vehicle 100. The ECU 181 controls the engine 102, transmission 103, or brakes based on the command value for speed change, thereby changing the speed of the work vehicle 100.

[0095] The ECU 182 controls the hydraulic system or electric motor included in the steering system 106 based on the measurements from the wheel sensor 152. This adjusts the steering angle of the steering wheels. The ECU182 controls the steering device 106 based on the command value for changing the steering angle, thereby changing the steering angle.

[0096] The ECU183 controls the movement of the three-point linkage and PTO shaft, etc., included in the coupling device 108, in order to cause the implement 300 to perform the desired operation. The ECU 183 generates a signal to control the operation of the implement 300 and transmits that signal from the communication device 190 to the implement 300.

[0097] The ECU184 performs calculations and control to realize autonomous driving based on output signals from the positioning device 110, steering wheel sensor 152, steering angle sensor 154, and axle sensor 156. During autonomous driving, ECU184 transmits a command value for speed change to ECU181 and a command value for steering angle change to ECU182. ECU184 controls the drive unit 240 to drive the work vehicle 100 along the target path.

[0098] If the automated driving plan includes a target route for the work vehicle 100, the ECU 185 records that information in the storage device 170. If the automated driving plan includes a departure point and a destination, or if the automated driving plan does not include a target route for the work vehicle 100, the ECU 185 calculates, for example, the route that will take the shortest time to reach the destination as the target route based on an environmental map containing road information stored in the storage device 170, and records that information in the storage device 170.

[0099] The ECU 186 estimates the status of the work vehicle 100 or implement 300 based on the output signal of the status detection device 230 and determines whether or not preparatory work is required. Once ECU186 determines that no preparatory work is required, it determines that the vehicle is ready for autonomous and remote driving. In other words, ECU186 accepts the reception of autonomous driving plans and requests for remote driving.

[0100] Through the cooperation of the above-mentioned ECUs 181 to 186, the control device 180 becomes capable of performing autonomous driving, creating target routes, and communicating with other devices. During autonomous driving, the control device 180 controls the drive unit 240 based on the position of the work vehicle 100 measured or estimated by the positioning device 110 and the target path stored in the storage device 170. This allows the control device 180 to drive the work vehicle 100 along the target path.

[0101] Multiple ECUs 181 to 186 included in the control unit 180 communicate according to a communication protocol such as CAN (Controller Area Network). Instead of CAN, a faster communication method such as Automotive Ethernet (registered trademark) may be used. In Figure 3, multiple ECUs 181-186 are shown as separate blocks, but their respective functions may be combined into a single ECU. Alternatively, an on-board computer may be provided that integrates at least some of the functions of multiple ECUs 181-186.

[0102] The communication device 190 includes a communication interface that performs, for example, the transmission and reception of signals compliant with the ISOBUS standard to the communication device 390 of the implement 300. This allows the implement 300 to perform desired actions or to retrieve information from the implement 300.

[0103] The communication device 190 also includes a communication interface that transmits and receives signals via the network 800 between the communication devices of the management terminal 400, the remote terminal 500, and the management server 600. Network 800 includes, for example, cellular mobile communication networks such as 3G, LTE, or 5G, and the Internet.

[0104] The operating terminal 200 is a terminal for performing operations related to the movement of the work vehicle 100 and the implement 300. It is also called a virtual terminal (VT). The operating terminal 200 is, for example, a tablet-type terminal device equipped with a display device such as a touchscreen and / or one or more operation buttons. The display device is, for example, a liquid crystal or organic light-emitting diode (OLED) display.

[0105] The passenger can use the control terminal 200 to perform various operations such as switching the automatic driving mode on / off, recording or editing the environmental map, setting a target route, and switching the implement 300 on / off. At least some of these operations can also be performed by operating the control switch group 210. The control terminal 200 can also be configured to be detachable from the work vehicle 100. In this case, the detached control terminal 200 communicates with the communication device 190 using a short-range communication method.

[0106] Therefore, by using the operation terminal 200 removed from the work vehicle 100, an operating user 510 located away from the work vehicle 100 can remotely control the work vehicle 100. Therefore, users who remotely operate the work vehicle 100 may include not only operating users 510 who use the remote terminal 500, but also users who remotely operate the work vehicle 100 using the operating terminal 200 removed from the work vehicle 100.

[0107] The drive unit 340 of the implement 300 performs the operations necessary for the implement 300 to perform a predetermined task. The drive unit 340 includes, for example, a hydraulic system, an electric motor, or a pump, depending on the application of the implement 300. The control device 380 controls the operation of the drive unit 340. The control device 380 responds to signals transmitted from the work vehicle 100 via the communication device 390 and causes the drive unit 340 to perform various operations.

[0108] [Example of a virtual terminal structure] Figure 4 is a perspective view showing an example of an operating terminal 200 and a group of operating switches 210 installed inside the cabin 105. Inside the cabin 105, a group of switches 210, which includes multiple switches that can be operated by the user, is arranged. The group of control switches 210 includes a switch for selecting the gear ratio of the main or sub-transmission, a mode switch for switching between automatic and manual driving modes, a forward / reverse switch for switching between forward and reverse, and an up / down switch for raising or lowering the implement 300.

[0109] [Internal configuration of the management device, management terminal, and remote terminal] Figure 5 is a block diagram showing an example of the internal configuration of the management server 600, the management terminal 400, and the remote terminal 500. As shown in Figure 5, the management server 600 comprises a storage device 650, a processor 660, a ROM (Read Only Memory) 670, a RAM (Random Access Memory) 680, and a communication device 690. These components are connected via a bus for communication.

[0110] The storage device 650 primarily functions as database storage and is, for example, a magnetic storage device or a semiconductor storage device. An example of a magnetic storage device is a hard disk drive (HDD), and an example of a semiconductor storage device is a solid-state drive (SSD). The storage device 650 may be a separate device, distinct from the enclosure of the management server 600. For example, the storage device 650 may be a storage device connected to the management server 600 via the network 800, such as a cloud storage device.

[0111] The processor 660 is, for example, an integrated circuit having a central processing unit (CPU). Specifically, in addition to the CPU, the processor 660 includes an FPGA (Field Programmable Gate Array), a GPU (Graphics Processing Unit), an ACIC (Application Specific Integrated Circuit), an ASSP (Application Specific Standard Product), or a combination of two or more integrated circuits selected from these. The processor 660 executes a computer program stored in the ROM 670 and performs predetermined processing.

[0112] ROM670 can be, for example, writable memory (e.g., PROM), rewritable memory (e.g., flash memory), or read-only memory. ROM670 stores programs that control the operation of processor 660. ROM670 is not limited to a single storage medium; it may be a collection of multiple storage media. Some of these storage media may be removable memory.

[0113] RAM680 provides a workspace for temporarily unpacking computer programs stored in ROM670 at startup. RAM680 is not limited to a single storage medium; it may also be a collection of multiple storage media.

[0114] The communication device 690 is a communication module for communicating with the work vehicle 100, the management terminal 400, and the remote terminal 500 via the network 800. The communication device 690 is capable of wired communication compliant with communication standards such as IEEE1394 (registered trademark) or Ethernet (registered trademark). The communication device 690 may perform wireless communication compliant with the Bluetooth (registered trademark) standard or the Wi-Fi standard, or cellular mobile communication such as 3G, 4G, or 5G.

[0115] As shown in Figure 5, the storage device 660 includes the actuals database DB1 and the planning database DB2. The performance database DB1 is a storage area for performance data received from agricultural machinery such as work vehicles 100. The performance data is stored in the performance database DB1, for example, categorized by agricultural machinery identification information. The planning database DB2 is a storage area for planning data necessary for creating automated driving plans. The planning data is stored in the planning database DB2, for example, categorized into static data and dynamic data.

[0116] As shown in Figure 5, the management terminal 400 comprises an input device 420, a display device 430, a storage device 450, a processor (processing unit) 460, a ROM 470, a RAM 480, and a communication device 490. These components are connected via a bus for communication. The input device 420 is a device that accepts input operations from the management user 410, and is, for example, a keyboard, mouse, or touch panel. The display device 430 is, for example, a liquid crystal display or an organic EL display.

[0117] The contents of the processor 460, ROM 470, RAM 480, storage device 450, and communication device 490 of the management terminal 400 are almost the same as those of the management server 600, so a detailed explanation will be omitted.

[0118] As shown in Figure 5, the remote terminal 500 includes an input device 520, a display device 530, a storage device 550, a processor (processing unit) 560, a ROM 570, a RAM 580, and a communication device 590. These components are connected to each other via a bus so that they can communicate with one another. The input device 520 is a device that receives input operations from the operating user 510, and is, for example, a keyboard, mouse, or touch panel. The display device 530 is, for example, a liquid crystal display or an organic EL display.

[0119] The contents of the processor 560, ROM 570, RAM 580, storage device 550, and communication device 590 of the remote terminal 500 are almost the same as those of the management server 600, so a detailed explanation will be omitted.

[0120] A control device 540 used for remotely controlling the work vehicle 100 is connected to the remote terminal 500. The control device 540 is an emulator of actual driving operations for the work vehicle 100 and has control devices (such as a steering wheel) that are equivalent to or similar to those used for manual driving. Furthermore, the operating device 540 also includes an interface that allows for operations equivalent to those of the operating terminal 200 and the group of operating switches 210. Therefore, the operating user 510 using the remote terminal 500 can remotely issue instructions to switch between manual and automatic operation.

[0121] [Procedure for creating an autonomous driving plan] Figure 6 is an explanatory diagram showing an example of the information setting screen 40 and information processing necessary for creating the automated driving plan P. The settings screen 40 in Figure 6 is displayed on the display device 430 of the management terminal 400 to accept input of setting information from the management user 410. Specifically, the processor 660 of the management server 600 instructs the management terminal 400 to display the settings screen 40 in Figure 6 in response to a creation request from the logged-in management terminal 400.

[0122] As shown in Figure 6, the settings screen 40 includes items such as a date display section 41, a farm map 42, a usage plan 43, farm equipment information 44, and a registration button 45. The date display section 41 is an item that displays the date of the day the settings screen 40 was opened. The farm map 42 is an item that displays a digital map of the real estate (for example, fields, barns, and farm equipment warehouses, etc.) included in the farm managed by the administrator user 410.

[0123] The storage device 650 of the management server 600 stores the equipment table T1, which contains equipment data for the farm managed by the management user 410. The equipment table T1 is pre-registered in the storage device 650 of the management server 600 via a settings screen different from that shown in Figure 6. In this case, the processor 660 of the management server 600 transmits the location information of each piece of equipment included in the equipment table T1 to the management terminal 400. The processor 460 of the management terminal 400 obtains a digital map corresponding to the received location information from a map distribution server or the like, and displays the obtained digital map within the frame of the farm map 42.

[0124] The equipment table T1 is a matrix-formatted data set in which, for example, a "label" and "label location" are defined for each given location ID. The "label" represents the type of property included in the farm, and the "label location" represents the location information (GNSS coordinates) of the property. The labels for barns and agricultural warehouses indicate GNSS coordinate values ​​(such as latitude and longitude). The labels for fields indicate a set of coordinates that can identify the boundary line representing the outer edge of the field. This set of coordinates consists, for example, of GNSS coordinate values ​​(such as latitude and longitude) of a cloud of points arranged at predetermined intervals along the outer edge of the field.

[0125] Utilization plan 43 is an item for defining the farm utilization plan envisioned by the management user 410. Utilization plan 43 includes, for example, the utilization period for fields A to D included in the farm, and the types of crops to be cultivated in each field A to D within that utilization period. In the example in Figure 6, "tomatoes" are set as the crop to be cultivated in field A, and "Koshihikari rice" is set as the crop to be cultivated in fields B, C, and D.

[0126] Agricultural machinery information 44 is an item for setting the type of agricultural machinery that can be used on the farm (tractor 100 and rice transplanter, etc.) and the implement 300 that can be attached to the tractor 100. The registration button 45 is a button that commands the transmission of the entered setting information. The configuration information entered in the usage plan 43 and the agricultural machinery information 44 is sent to the management server 600. Based on the received configuration information, the processor 660 of the management server 600 creates an automated operation plan P for each agricultural machinery defined in the agricultural machinery information 44, in accordance with the usage plan 43 formulated by the management user 410.

[0127] The processor 660 of the management server 600 temporarily stores the automated operation plan P for each agricultural machine that it has created in the planning database DB2 of the storage device 650. The processor 660 of the management server 600, in response to a transmission request from an agricultural machine with a predetermined agricultural machine ID, extracts an automated driving plan P related to the transmitting agricultural machine ID from the planning database DB2 using the storage device 650, and transmits the extracted automated driving plan P to that agricultural machine ID.

[0128] As shown in Figure 6, the process of creating the automated driving plan P performed by the processor 660 of the management server 600 includes the following first to fourth processes. Process 1: Creation of work cost table T2 Second process: Creation of the farm equipment status table T3 Third step: Creating the remaining task table T4 Process 4: Calculation of the Automated Driving Plan P The contents of the first to fourth processes are explained below.

[0129] (First process) The first process is to create a "work cost table T2" ​​which compiles work cost data related to the costs of each operation that can be performed on the farm, based on the usage plan 43, farm machinery information 44, and equipment data (equipment table T1) set by the management user 410. Figure 7 shows an example of a work cost table T2. As shown in Figure 7, the work cost table T2 consists of matrix-formatted data in which, for example, "label," "task," "required time," "farm equipment constraints," and "weather constraints" are defined for each work ID.

[0130] In the work cost table T2, the "label" column indicates the type of real estate included in the label in the equipment table T1. The "work" column indicates the type of work required for each label (e.g., tilling and ridging) that is necessary for cultivating the crop set out in the utilization plan 43. The "Required Time" column shows the time required for each task. Field work time is calculated based on the field area and other factors identified from equipment table T1. The "Agricultural Machinery Constraints" column shows the types of implements and agricultural machinery required for the work. The "Weather Constraints" column shows the types of weather conditions under which field work can be performed.

[0131] As shown in Figure 7, a field work ID is associated with a field map Mi (where i is the work ID). The field map Mi defines a standard target route for each type of work performed in the field, when the work vehicle 100 is driven automatically. For example, in the example shown in Figure 7, the target paths for each field map i are as follows: Field Map M001: Target work route when tilling field A. Field Map M002: Target route for work when creating ridges in Field A. Field Map M003: Target route for work vehicle operation when tilling field B.

[0132] (Second process) The second process is to create a "Farm Machinery Status Table T3" which summarizes the current status data of agricultural machinery included in the farm machinery information 44, based on the farm machinery information 44 set by the management user 410. Figure 8 shows an example of the agricultural machinery status table T3. As shown in Figure 8, the agricultural machinery status table T3 consists of matrix-formatted data in which, for example, "type," "installable impulses," "currently installed impulses," "current location (GNSS location)," and "current status" are defined for each agricultural machinery ID.

[0133] In the farm equipment status table T3, the "Type" column displays the type of farm equipment set in farm equipment information 44. The "Compatible Implements" column displays the identification information of implements 300 that can be attached to farm equipment (tractor 100) that requires implements 300. The "Installed Implement" field displays the identification information of the implement 300 currently installed on the tractor 100. The "Current Location" field displays the current location information of the farm machine. The "Current Status" field displays the current operating mode of the farm machine (e.g., automatic or remote operation). The identification information of the installed implement 300, the farm machine's location information, and the operating mode are obtained by the management server 600 by querying the farm machine.

[0134] (Third process) The third process is to create a "remaining task table T4" which summarizes the remaining task data regarding the progress of tasks that make up the automated driving plan P, based on the usage plan 43 set by the management user 410 and the work cost data (work cost table T3). Figure 9 shows an example of a remaining tasks table T4. As shown in Figure 9, the remaining tasks table T4 consists of matrix-formatted data in which, for example, the "corresponding task ID," "status," and "duration to be completed" are defined for each task ID.

[0135] In the remaining tasks table T4, the "corresponding task ID" is the task ID from the task cost table T3 that is associated with the task ID. The "Status" field displays information that identifies whether the task is complete or incomplete (e.g., "Completed," "Available," or "Not Available"). Here, "Completed" means the task is finished. "Available" means the task is incomplete and therefore available for selection.

[0136] "Not Selectable" means that the task is incomplete, but cannot be selected to be included in the autonomous driving plan due to certain constraints such as weather conditions. The processor 660 of the management server 600 monitors the status of task IDs in the remaining task table T3. When any of the tasks among the multiple task IDs whose status is selectable is completed, the processor changes the status of the completed task ID to "Completed".

[0137] The "Period to be implemented" specifies the start and end dates of the task. The processor 660 of the management server 600 determines the period during which the task should be implemented, within the usage period defined in the usage plan 43. For example, the storage device 650 of the management server 600 stores the optimal time to perform the work (e.g., the time for preparing furrows) for each type of crop. In this case, the processor 660 of the management server 600 adopts the preferred execution time read from the storage device 650 as the period to be recorded in the execution period of the remaining task table T4.

[0138] (Fourth process) The fourth process is to calculate the automatic operation plan P for each agricultural machine ID based on equipment data (equipment table T1), agricultural machine status data (agricultural machine status table T3), and remaining task data (remaining task table T4). Figure 10 shows an example of an automated driving plan P for a single agricultural machine. As shown in Figure 10, the automated driving plan P for the agricultural machine (here, the agricultural machine ID is assumed to be "001") consists of matrix-formatted data that defines, for example, "date," "time," "work content," and "corresponding task ID."

[0139] In the autonomous driving plan P, the "Year, Month, and Day" field indicates the date on which agricultural machine 001 will operate autonomously. The "Time" field indicates the time period during which agricultural machine 001 will operate autonomously. The "Work Details" field describes the details of the automated operation performed by agricultural machine 001. The "Corresponding Task ID" field contains the task ID from the remaining task table T4 that is associated with the work details. In the fourth process, the processor 660 of the management server 600 calculates an automated operation plan P to complete the tasks in the remaining task table T4 within the time period during which they should be performed.

[0140] Specifically, under the constraint that the remaining tasks in the task table T4 must be completed within the specified time period, the processor 660 selects the combination of predetermined explanatory variables that minimizes a predetermined cost from among all possible combinations, and uses this as the automated operation plan P for the agricultural machine 001. Furthermore, if there are constraints on the timing of the work (such as the season) or weather conditions, the processor 660 will also adopt those constraints as conditions.

[0141] Examples of explanatory variables used above include the travel time required for inter-field movement and the time required as defined in the work cost table T2 (e.g., the time required for field work). In this case, the processor 660 determines the combination of route and work ID that minimizes the sum of the travel time and required time of the agricultural machine 001 as the automated driving plan P for the agricultural machine 001.

[0142] Alternatively, the distance traveled by the farm machine can be used as an explanatory variable. In this case, the processor 660 selects the route and work ID combination that minimizes the total travel distance from the farm machine's current position to the target point from all possible routes, and defines this as the automated driving plan P. If the agricultural machine is a tractor 100, the number of implement replacements may be used as the explanatory variable described above. In this case, the processor 660 sets the combination of route and work ID that minimizes the number of implement replacements as the automatic driving plan P for the agricultural machine 001.

[0143] [Processing for switching driving modes by work vehicles] Figure 11 is a state transition diagram showing an example of the driving mode switching process performed by the control device (electronic control unit) 180 of the work vehicle 100. As shown in Figure 11, the control status of the driving mode includes the following states S1 to S4. Note that "Plan P1" below is the automated driving plan created by the management server 600, and "Plan P2" below is the automated driving plan created by the remote terminal 500. State S1: Automated driving 1 (Automated driving based on plan P1) Status S2: Remote Operation Status S3: Manual Operation State S4: Autonomous driving 2 (Autonomous driving based on plan P2)

[0144] The switch from state S1 to state S2 is triggered by the fulfillment of condition C1. Condition C1 is a type of "intervention" in the automated driving process that follows the automated driving plan P. Condition C1 includes, at a minimum, the receipt of a remote start request, the stabilization of the communication status, and the cessation of operation of the work vehicle 100. A remote start request is a communication message sent from the remote terminal 500 to the work vehicle 100, requesting the work vehicle 100 to start remote operation. The stability of the communication state is determined, for example, by the level of RSSI (Received Signal Strength Indicator), SNR (Signal Noise Rate), or bit error rate measured by the communication device 190.

[0145] The cessation of operation of the work vehicle 100 means that, with the IG power on, the work vehicle 100 is not moving and the implement 300 is not being driven. The decision to stop the operation of the work vehicle 100 is made based on factors such as the length of time the vehicle has been at zero speed and whether or not the brakes have been applied.

[0146] The switch from state S2 to state S1 is triggered by the fulfillment of condition C2. Condition C2 is a type of "deactivation of intervention" in autonomous driving according to the autonomous driving plan P. Condition C2 includes, at a minimum, the receipt of a remote termination request, the ability to operate autonomously, and the cessation of operation of the work vehicle 100.

[0147] A remote termination request is a communication message sent from the remote terminal 500 to the work vehicle 100, requesting the work vehicle 100 to terminate remote operation. The state in which autonomous driving is possible can be determined, for example, when the state estimation ECU186 determines that no preparation work is required. The method for determining when operation should be stopped is the same as described above.

[0148] The switch from state S1 to state S3 is triggered by the fulfillment of condition C3. Condition C3 is a type of "intervention" to the automated driving system that follows the automated driving plan P. Condition C3 includes, at a minimum, the detection of direct manipulation by a person on board. Direct operation includes, for example, operating the brake pedal, operating the accelerator pedal, and operating the steering wheel, at least one operation that is intentionally and physically performed by a person attempting to drive the work vehicle 100.

[0149] The switch from state S3 to state S1 is triggered by the fulfillment of condition C4. Condition C4 is a type of "deactivation of intervention" in autonomous driving according to the autonomous driving plan P. Condition C4 includes, at a minimum, being undetectable for a predetermined period of direct operation (e.g., 20 seconds), being in a state where automatic driving is possible, and having stopped moving. The method for determining whether automatic driving is possible and the method for determining whether the vehicle is moving are the same as described above.

[0150] The switch from state S1 to state S4 is triggered by the fulfillment of condition C5. Condition C5 is, for example, the transmission of a "change response". The change response is a response message to the remote terminal 500, which is the source of the change request from plan P1 to plan P2. The switch from state S4 to state S1 is triggered by the fulfillment of condition C6. Condition C6 is, for example, the transmission of a "completion notification". The completion notification is a message sent to the remote terminal 500, which is the source of the change request for plan P2, notifying it that the automated operation in accordance with plan P2 has been completed.

[0151] In Figure 11, data D1 is the actual data collected by the control device 180 during the period of automated driving 1 (automated driving according to the plan P1 of the management server 600). Data D2 is the actual data collected by the control device 180 during the period of manual driving. Data D3 is the actual data collected by the control device 180 during the remote operation period. Data D4 is the actual data collected by the control device 180 during the automated operation 2 period (autonomous operation according to the remote device 500's plan P2).

[0152] The performance data D1 to D4 are transmitted to the control device 600. The transmission cycle for the performance data D1 to D4 may be every predetermined time (for example, every few seconds to every few minutes), or the performance data for the previous mode may be transmitted all at once after the operating mode is switched. The processor 660 of the management device 600 stores the received performance data D1 to D4 in the performance database DB1 of the storage device 650. The processor 660 can also use the performance data D2 to D4 for updating planning data, etc. (see Figure 14).

[0153] [Communication sequence for plan changes] Figure 12 is a sequence diagram showing an example of a communication sequence for a plan change executed between three parties: the management terminal 400, the management server 600, and the work vehicle 100. In Figure 12, "P1" is the automated driving plan created by the management server 600, and "P2" is the automated driving plan created by the remote terminal 500. Furthermore, although the remote terminal 500, management server 600, and work vehicle 100 are described below as the executing entities, the actual executing entities are their processors 460, processor 660, and control device 180.

[0154] As shown in Figure 12, here we assume that when the work vehicle 100 is performing automated driving according to plan P1 (step S10), the remote terminal 500 sends a change request message including plan P2 to the work vehicle 100 (step S11). In this case, the work vehicle 100 sends a change response message to the remote terminal 500 (step S12) and a change notification message including the plan P2 to the management server 600 (step S13).

[0155] Next, the work vehicle 100 changes the referenced automated driving plan from plan P1 to plan P2 (step S14), and performs automated driving according to plan P2 (step S16). Upon receiving the change notification message, the management server 600 changes the automated driving plan from the plan P1 it created to the notified plan P2 (step S17), and waits for the completion of plan P2 (step S17).

[0156] Next, when the work vehicle 100 completes the automated driving according to plan P2, it sends a completion notification message to the remote terminal 500 and the management server 600 (step S18). Subsequently, the work vehicle 100 creates performance data D4 (step S19) and sends the created performance data D4 to the management server 600 (step S20).

[0157] The performance data D4 is the performance data collected by the control device 180 of the work vehicle 100 during the period of automated driving according to the plan P2 created by the remote terminal 500. The management server 600 stores the received performance data D4 in the performance database DB1 of the storage device 650 and, if necessary, recalculates the automated driving plan P (step S21: see Figure 14).

[0158] [Examples of work changes due to plan changes] Figure 13 is an explanatory diagram showing an example of changes to field work due to a change in the plan. In the example shown in Figure 13, the management server 600's plan P1 includes a task to sequentially create furrows U1 to U6 in the field, while the remote terminal 500's plan P2 includes a task to skip the second furrow U2 and move from furrow U1 to furrow U3.

[0159] In this case, the control device 180 of the work vehicle 100 creates a target route for working in the field according to the task of plan P2, and controls the work vehicle 100 to move along the created target route. The control device 180 also collects actual data D4 during the work run. Therefore, the performance data D4 collected by the control device 180 will include data such as movement trajectory data collected during work travel along a route that skips the ridges U2.

[0160] [Data storage and updating by a management device] Figure 14 is a flowchart showing an example of data storage and updating by the management server 600. As shown in Figure 14, the processor 660 of the management server 600 monitors whether or not it has received performance data D2 to D4 from the work vehicle 100 (step S31). If it has received the data, it stores the received performance data D2 to D4 in the performance database DB1 of the storage device 650 (step S32).

[0161] As mentioned above, performance data D2 is the performance data during the remote driving period. Performance data D3 is the performance data during the manual driving period. In addition, performance data D4 is the performance data during the automated driving period according to the automated driving plan P2 created by the remote terminal 500. Furthermore, the processor 660 also stores the actual data D1 from the period of autonomous driving according to the autonomous driving plan P1 it created in the actual database DB1 of the storage device 650.

[0162] Next, processor 660 determines whether there is any data in the planning database DB2 that needs updating (step ST33). Specifically, processor 660 determines whether or not the dynamic data managed in the planning database DB2 needs to be updated, in addition to the static data. This is because static data is data whose content does not change even when the operating mode changes.

[0163] If the result of step S33 is positive, the processor 660 performs an update of the planning data (step S34). Specifically, the processor 660 updates the dynamic data that it has determined needs updating. If the result of the determination in step S33 is negative, the processor 660 skips step S34 and proceeds with processing.

[0164] Next, the processor 660 determines whether or not to recalculate the automated driving plan P (step ST35). This determination is made, for example, based on whether or not the dynamic data has been updated. Alternatively, a request for transmission of the automated driving plan from the work vehicle 100 may be used as a weighted condition. If the result of step S35 is positive, the processor 660 recalculates the automated driving plan P (step S35). Specifically, the processor 660 uses the updated dynamic data to recalculate the plan P. If the result of step S35 is negative, the processor 660 skips step S36 and terminates the process.

[0165] [Specific examples of work changes after intervention] Figure 15 is an explanatory diagram illustrating an example of a change in work after remote operation intervention. Here, we assume that the following events E1 to E7 occur during the execution of the first task (movement from barn A to field A between 7:00 and 8:00) of a work vehicle 100 (hereinafter referred to as "farm vehicle 100") whose farm equipment ID is "100" and which has acquired the automated driving plan P shown in Figure 10.

[0166] Event E1: Remote start request received at 7:30 (intervention) Event E2: Move to field C via remote control from 7:30 to 9:00. Event E3: Work will be carried out in field C via remote operation from 9:00 to 14:00. Event E4:14:00 received remote termination request (intervention terminated). Event E5: From 14:00 to 14:10, the vehicle will move from field C to field B via automated operation. Event E6: From 14:10 to 18:10, work will be carried out in field B using automated operation. Event E7: From 18:10 to 19:30, the vehicle will move from field B to barn A via automated driving.

[0167] In this case, the remote termination request (event E4) is notified to the control device 600 either directly or via the farm machine 100, and immediately after event E4, the farm machine 100 obtains the automated driving plan P recalculated by the control device 600. As shown in Figure 15, after the occurrence of E1, the agricultural machine 100 moves to field C from the location where E1 occurred via remote control (E2), and performs predetermined work on field C via remote control by the operating user 510 (E3).

[0168] After the occurrence of E4, the farm machine 100 moves from field C to field B (E5) by automatic operation in accordance with the automatic operation plan P newly acquired from the management device 600, and performs the prescribed work on field B by the same automatic operation (E6). Subsequently, the farm machine 100 moves from field B to barn A by automatic operation in accordance with the newly acquired automatic operation plan P from the management device 600 (E7).

[0169] [Example of updating planning data] Figure 16 is an explanatory diagram showing an example of updating the agricultural machinery status table T3, which is performed as a result of event E4 in Figure 15. As mentioned above, event E4 in Figure 15 is work performed in field C by remote operation, so the current location of the farm machine 100 is within field C, and the operating mode of the farm machine 100 is remote operation.

[0170] Therefore, the current position in the farm equipment status table T3 is updated from the coordinate values ​​along the route from barn A to field A to the coordinate values ​​within field C, and the current status in the farm equipment status table T3 is updated from "in automatic operation" to, for example, "preparing for automatic operation." The performance data D2 collected by the agricultural machine 100 includes not only movement performance data, but also measurement data and control performance data. Therefore, the processor 660 of the management device 600 may estimate the work performed remotely in field C based on, for example, whether or not the PTO was used, whether or not double speed was used, and the history of GNSS position.

[0171] Furthermore, if the details of the work performed remotely are notified to the management device 600 by the operator 510 via input to the remote terminal 500, the processor 660 of the management device 600 will be able to directly identify the work performed in field C. Thus, if the processor 660 can identify the work being done on field C remotely, the currently installed integrator on the farm equipment status table T3 should be changed to the integrator corresponding to the identified work.

[0172] Figure 17 is an explanatory diagram illustrating an example of updating the remaining tasks table T4, which is performed as a result of event E4 in Figure 15. Here, for example, let's assume that the corresponding task ID for the work performed in field C for event E4, as identified by the processor 660 of the control device 600, is "task 007".

[0173] In this case, if there is a task ID (task 005 in the diagram) whose corresponding work ID is work 007 and whose status is "selectable", processor 660 updates the status of that task ID to "completed". In addition, the status of subsequent task IDs is also updated from not selectable to selectable. This prevents completed tasks from being mistakenly included in the recalculated automated driving plan P as remaining tasks.

[0174] Furthermore, the management device 600 may manage the work route of the field map Mi (see Figure 7) corresponding to the work ID as actual data. In this case, the processor 660 of the management device 600 may save the work route of the farm machine 100 obtained during the remote operation of event E4 as actual data for the field map M007 of work 007.

[0175] [Example of recalculating an autonomous driving plan] Figure 18 is an explanatory diagram showing an example of an automated driving plan P created by recalculation. In Figure 18, "Pa" is the original plan before event E4, and "Pb" is the plan created by recalculating after event E4. As mentioned above, the calculation of Plan P uses the equipment table T1, the current agricultural machinery table T3, and the remaining tasks table T4 (Fourth process in Figure 6). Therefore, if at least one of the current agricultural machinery table T3 and the remaining tasks table T4 is updated, the content of Plan P may also change.

[0176] In the example in Figure 15, the distance traveled from field C to field B is significantly shorter than the distance traveled from field C to field A. Therefore, when event E4 (cancellation of intervention) occurs, it is more advantageous in terms of cost, such as time or distance, to head to the closer field B rather than to the further field A according to the original plan Pa. Therefore, as shown in Figure 18, if processor 660 performs a recalculation (fourth process) at the time event E4 occurs, an efficient plan Pb including events E5, E6, and E7 can be created.

[0177] [Example format for performance data] Figure 19 shows an example of movement trajectory data D11 stored in the performance database DB1 of the management server 600. As shown in Figure 19, the movement trajectory data D11 is time-series data of the tractor 100's position information, and includes the "farm machine position" (latitude and longitude) and "driving mode" for each time period. In the case of the work vehicle 100, the farm machine position may also be the position of the implement 300.

[0178] The operating mode in the movement trajectory data D11 contains identification information representing the type of operating mode of the work vehicle 100 at each time point progressing within a predetermined sampling period. In the example in Figure 19, the operating mode started at time t1 is "Automatic Operation (Management Server)", the operating mode started at time t11 is "Remote Operation", and the operating mode started at time t101 is "Automatic Operation (Management Server)".

[0179] In this embodiment, not only does the management server 600 provide the work vehicle 100 with an automated driving plan P1, but the remote terminal 500 can also provide the work vehicle 100 with an automated driving plan P2 that it has created itself, allowing the plan to be modified midway (see Figure 12). Therefore, the "autonomous driving" in the driving mode of the movement trajectory data D11 is defined in a way that allows identification of whether the autonomous driving conforms to plan P1 or plan P2. In the example in Figure 19, both the autonomous driving starting at time t1 and the autonomous driving starting at time t101 are autonomous driving according to plan P1 of the management server 600.

[0180] Figure 20 shows an example of work performance data D12 stored in the performance database DB1 of the management device 600. As shown in Figure 20, the movement trajectory data D11 is time-series data of the work performance of the work vehicle 100, and includes "work performance" and "driving mode" for each time period. The work performance includes, as an example, "vehicle speed," "PTO rotation speed," and "fertilizer application amount."

[0181] The operating mode in the work performance data D12 also includes identification information that represents the type of operating mode of the work vehicle 100 at each time point progressing according to a predetermined sampling period. The "Automated Driving" section of the work performance data D12 is also defined in a way that allows for identification of whether the automated driving is based on plan P1 or plan P2. In the example in Figure 20, the automated driving that starts at 98:10:10 is automated driving according to plan P1 of the management server 600, and the automated driving that starts at 98:40:13 is automated driving according to plan P2 of the remote terminal 500.

[0182] [Other variations] The embodiments disclosed herein are illustrative and not restrictive in all respects. The scope of the present invention is not limited to the embodiments described above, and includes all modifications within the scope equivalent to the configurations described in the claims. [Explanation of symbols]

[0183] 40 Settings screen 41 Date display section 42 Farm Map 43. Usage Plan 44 Agricultural machinery information 45. Register button 100 Work vehicles (tractors) 101 Vehicle body 102 Prime mover (engine) 103 Transmission 104 Tires (wheels) 105 Cabin 106 Steering gear 107 Driver's seat 110 Positioning device 111 GNSS receiver 112 RTK receiver 115 IMU 116 Processing Circuit 120 Cameras 130 Obstacle Sensor 140 LiDAR sensors 150 Sensors 152 Steering wheel sensor 154 Steering Angle Sensor 156 Axle Sensor 160 Control Systems 170 Storage device 180 Electronic control unit 181 ECU (Speed ​​Control Unit) 182 ECU (Steering Control) 183 ECU (Implement Control Unit) 184 ECU (Automated Control Unit) 185 ECU (route creation) 186 ECU (State Estimation) 190 Communication equipment 200 Operating terminals 210 switch group 220 Buzzer 230 State detection device 240 Drive unit 300 implements 340 Drive unit 380 Control Device 390 Communication Device 400 First Terminal Device (Management Terminal) 410 Management User 420 Input Device 430 Display Device 450 Storage Device 460 Processor 470 ROM 480 RAM 490 Communication Device 500 Second Terminal Device (Remote Terminal) 510 Operating User 520 Input Device 530 Display Device 540 Operating Device 550 Storage Device 560 Processor 570 ROM 580 RAM 590 Communication Device 600 Management Device 650 Storage Device 660 Processor 670 ROM 680 RAM 690 Communication Device 800 Network 900 Management System T1 Equipment Table (Equipment Data) T2 Work Cost Table (Work Cost Data) T3 Agricultural Machinery Status Table (Agricultural Machinery Status Data) T4 Remaining Task Table (Remaining Task Data) P Automatic Driving Plan P1 Automatic Driving Plan P2 Automatic Driving Plan

Claims

1. A control device that communicates with agricultural machinery whose operating modes include automatic and non-automatic operation, A processing device for creating an automated driving plan for the aforementioned agricultural machinery, A communication device that transmits the aforementioned automated driving plan to the agricultural machine and receives the performance data of the agricultural machine collected by the agricultural machine, The system includes a storage device for storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes manual operation in which a human directly operates the agricultural machinery, The aforementioned intervention in manual operation is Conditional on detecting direct human intervention, The release of the intervention in the manual operation is A control device that is subject to the conditions of no detection for a predetermined period of time during the direct operation, a state in which automatic operation is possible, and the cessation of operation of the agricultural machinery.

2. The aforementioned performance data further, The management device according to claim 1, which includes data collected by the agricultural machine during modified automated driving that is performed in response to a change request that occurred during automated driving in accordance with the automated driving plan.

3. The aforementioned storage device is The management device according to claim 2, having a database in which the performance data is stored so as to be able to identify which of the following periods was collected: the period of automated driving in accordance with the automated driving plan, the period of manual driving, and the period of modified automated driving.

4. A control device that communicates with agricultural machinery whose operating modes include automatic and non-automatic operation, A processing device for creating an automated driving plan for the aforementioned agricultural machinery, A communication device that transmits the aforementioned automated driving plan to the agricultural machine and receives the performance data of the agricultural machine collected by the agricultural machine, The system includes a storage device for storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes remote operation, in which the agricultural machinery is remotely controlled using an operating terminal. The aforementioned remote driving intervention is A control device that is subject to the conditions of receiving a remote start request, stabilizing the communication status, and stopping the operation of the agricultural machinery.

5. The termination of the remote operation intervention is The management device according to claim 4, provided that a remote termination request is received, the device is in a state where automatic operation is possible, and the operation of the agricultural machinery is stopped.

6. A control device that communicates with agricultural machinery whose operating modes include automatic and non-automatic operation, A processing device for creating an automated driving plan for the aforementioned agricultural machinery, A communication device that transmits the aforementioned automated driving plan to the agricultural machine and receives the performance data of the agricultural machine collected by the agricultural machine, The system includes a storage device for storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes at least one of manual operation, in which a human directly operates the agricultural machinery, and remote operation, in which the agricultural machinery is remotely operated using an operating terminal. The aforementioned storage device is Further storing the planning data necessary for creating the aforementioned automated driving plan, The aforementioned processing apparatus is A management device that, when the planning data is updated after a change request occurs during the intervention or during autonomous driving in accordance with the autonomous driving plan, uses the updated planning data to create the autonomous driving plan to be created in the future.

7. The aforementioned planning data is Static data whose content does not change even when the aforementioned operating mode changes, This includes dynamic data whose content may change when the aforementioned operating mode changes, The management device according to claim 6, wherein the processing device is subject to updating when the intervention or change request is made.

8. The aforementioned static data is The management device according to claim 7, comprising at least one of the following: farm equipment data, farm utilization plan, and farm machinery information for the farm.

9. The aforementioned dynamic data is The management device according to claim 7, comprising at least one of the following: data representing the current status of the agricultural machinery and data representing the progress of the tasks constituting the automated driving plan.

10. A method for managing agricultural machinery, which includes automatic and non-automatic driving modes, and a management device that communicates with the agricultural machinery, wherein the management device performs the management of the agricultural machinery, The steps include creating an automated driving plan for the aforementioned agricultural machinery, The steps include transmitting the aforementioned automated driving plan to the agricultural machine, The steps include receiving performance data of the agricultural machinery collected by the aforementioned agricultural machinery, The steps include storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes manual operation in which a human directly operates the agricultural machinery, The aforementioned intervention in manual operation is Conditional on detecting direct human intervention, The release of the intervention in the manual operation is A management method that is conditional on the direct operation being undetectable for a predetermined period of time, the operation being possible automatically, and the operation of the agricultural machinery being stopped.

11. A method for managing agricultural machinery, which includes automatic and non-automatic driving modes, and a management device that communicates with the agricultural machinery, wherein the management device performs the management of the agricultural machinery, The steps include creating an automated driving plan for the aforementioned agricultural machinery, The steps include transmitting the aforementioned automated driving plan to the agricultural machine, The steps include receiving performance data of the agricultural machinery collected by the aforementioned agricultural machinery, The steps include storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes remote operation, in which the agricultural machinery is remotely controlled using an operating terminal. The aforementioned remote driving intervention is A management method that is conditional on receiving a remote start request, stabilizing the communication status, and stopping the operation of the agricultural machinery.

12. A method for managing agricultural machinery, which includes automatic and non-automatic driving modes, and a management device that communicates with the agricultural machinery, wherein the management device performs the management of the agricultural machinery, The steps include creating an automated driving plan for the aforementioned agricultural machinery, The steps include transmitting the aforementioned automated driving plan to the agricultural machine, The steps include receiving performance data of the agricultural machinery collected by the aforementioned agricultural machinery, The steps include storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, In the aforementioned storage step, Further storing the planning data necessary for creating the aforementioned automated driving plan, In the above creation step, A management method for using the updated planning data to create future automated driving plans when an update of the planning data is performed after a change request occurs during the intervention or automated driving in accordance with the automated driving plan.

13. A computer program for operating a computer as a management device that communicates with agricultural machinery whose operating modes include automatic and non-automatic operation, The steps include creating an automated driving plan for the aforementioned agricultural machinery, The steps include transmitting the aforementioned automated driving plan to the agricultural machine, The steps include receiving performance data of the agricultural machinery collected by the aforementioned agricultural machinery, The steps include storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes manual operation in which a human directly operates the agricultural machinery, The aforementioned intervention in manual operation is Conditional on detecting direct human intervention, The release of the intervention in the manual operation is A computer program that is subject to the conditions of no detection for a predetermined period of time during the direct operation, a state in which automatic operation is possible, and the cessation of operation of the agricultural machinery.

14. A computer program for operating a computer as a management device that communicates with agricultural machinery whose operating modes include automatic and non-automatic operation, The steps include creating an automated driving plan for the aforementioned agricultural machinery, The steps include transmitting the aforementioned automated driving plan to the agricultural machine, The steps include receiving performance data of the agricultural machinery collected by the aforementioned agricultural machinery, The steps include storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, The aforementioned non-autonomous driving is This includes remote operation, in which the agricultural machinery is remotely controlled using an operating terminal. The aforementioned remote driving intervention is A computer program that is conditional on receiving a remote start request, stabilizing the communication status, and stopping the operation of the agricultural machinery.

15. A computer program for operating a computer as a management device that communicates with agricultural machinery whose operating modes include automatic and non-automatic operation, The steps include creating an automated driving plan for the aforementioned agricultural machinery, The steps include transmitting the aforementioned automated driving plan to the agricultural machine, The steps include receiving performance data of the agricultural machinery collected by the aforementioned agricultural machinery, The steps include storing the received performance data, The aforementioned performance data is This includes data collected by the agricultural machinery during non-autonomous driving, which is performed as a result of interventions that occur during autonomous driving in accordance with the aforementioned autonomous driving plan, In the aforementioned storage step, Further storing the planning data necessary for creating the aforementioned automated driving plan, In the above creation step, A computer program that, when the planning data is updated after a change request occurs during the intervention or during autonomous driving in accordance with the autonomous driving plan, uses the updated planning data to create the autonomous driving plan to be created in the future.

16. Agricultural machinery that includes automatic and manual driving modes, A management system for agricultural machinery comprising a control device that communicates with the aforementioned agricultural machinery, The aforementioned control device is The automated driving plan for the agricultural machinery is transmitted to the agricultural machinery, The aforementioned agricultural machinery, If manual intervention occurs during automated driving in accordance with the aforementioned automated driving plan, the performance data of the vehicle collected during the manual driving is transmitted to the management device. The aforementioned control device is The received performance data during manual operation is stored in its own memory device. The aforementioned operating mode further includes: Including remote operation, The aforementioned management system further, Includes a remote terminal that communicates with the aforementioned agricultural machinery and causes the machinery to perform remote operation, The aforementioned agricultural machinery, If remote control intervention occurs during automated driving in accordance with the aforementioned automated driving plan, the performance data of the vehicle collected during said remote control is transmitted to the management device. The aforementioned control device is The received performance data during remote operation is stored in the device's own memory, The aforementioned remote terminal is It is possible to send a request for a change in autonomous driving to the agricultural machine. The aforementioned agricultural machinery, The performance data of the vehicle collected during the modified automated driving, which was carried out in response to the change request received during automated driving according to the automated driving plan, is transmitted to the management device. The aforementioned control device is A management system that stores the received, modified performance data during autonomous driving in its own storage device.

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