Location information providing device, location information providing method and program

Abstract

A position information providing device according to one aspect of the present disclosure is connected with a moving body comprising at least a GNSS receiver via a communication network, and comprises: a position measurement unit configured to measure the current position of the moving body on the basis of a GNSS signal received by the GNSS receiver; a prediction unit configured to predict a future position of the moving body on the basis of a movement history of the moving body and an operation plan of the moving body; and a providing unit configured to provide requested position information to a request source in accordance with a request for position information indicating the past, current, or future position of the moving body.

Description

[Technical Field]

[0001] The present disclosure relates to a location information providing device, a location information providing method, and a program. [Background technology]

[0002] In recent years, against the backdrop of a decline in the workforce in agricultural fields, research and demonstration experiments have been conducted on autonomous driving technologies for agricultural machinery (agricultural machines) such as tractors and combine harvesters (for example, Non-Patent Document 1). Elemental technologies related to the autonomous driving of such agricultural machinery include, for example, technology that predicts the destination of the agricultural machinery based on its movement history (i.e., information on the current and past locations of the agricultural machinery). Other technologies also exist, such as technology that estimates the network quality at the destination, technology that automatically reduces the speed or stops the agricultural machinery if the network quality at the destination is poor, and technology that analyzes images from cameras mounted on the agricultural machinery at the edge / cloud and notifies a remote control device or the like if any danger is detected. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] "Realizing autonomous inter-field navigation and remote monitoring control of agricultural machinery using robotic agricultural machinery, 5G, and IOWN-related technologies," NTT Technical Journal, March 2021 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the past, because the destination of agricultural machinery was predicted using only the movement history of the machinery, the predicted destination sometimes differed from the actual location of the machinery. This is because agricultural machinery generally moves according to an operation plan that takes into account the planting location within the field, etc. Therefore, it was not possible to estimate the network quality at the actual destination of the machinery, and as a result, it was sometimes impossible to control the speed of the machinery.

[0005] The present disclosure has been made in consideration of the above points, and aims to provide technology that can realize automatic driving of a moving object while also taking into account operation plans. [Means for solving the problem]

[0006] A location information providing device according to one aspect of the present disclosure is a location information providing device connected to a mobile body equipped with at least a GNSS receiver via a communication network, and includes: a positioning unit configured to position the current position of the mobile body based on a GNSS signal received by the GNSS receiver; a prediction unit configured to predict the future position of the mobile body based on the movement history of the mobile body and an operation plan of the mobile body; and a providing unit configured to provide the requested location information indicating the past, present, or future position of the mobile body to a requestor in response to a request for the location information. [Effects of the Invention]

[0007] This provides technology that enables autonomous driving of moving vehicles while taking operation plans into consideration. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 2 is a diagram for explaining an example of a movement path of an agricultural machine within a farm field. [Figure 2] FIG. 1 is a diagram illustrating an example of a predicted destination and a travel route according to the prior art. [Figure 3] 1 is a diagram illustrating an example of the overall configuration of an autonomous driving system according to an embodiment of the present invention. [Figure 4] FIG. 2 is a diagram illustrating an example of a functional configuration of the agricultural machine according to the present embodiment. [Figure 5] FIG. 2 is a diagram illustrating an example of a functional configuration of a location information providing server according to the present embodiment. [Figure 6] 10 is a flowchart illustrating an example of an operation plan data and position information data storage process according to the present embodiment. [Figure 7] 10 is a flowchart illustrating an example of a position information prediction process according to the present embodiment. [Figure 8]10 is a flowchart illustrating an example of a location information providing process according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] An embodiment of the present invention will be described below. In the following, the mobile object is assumed to be a drivable agricultural machine (e.g., a tractor, a combine harvester, a rice planter, etc.) used mainly for agricultural work in fields, and an automatic driving system 1 that can realize automatic driving taking into account the operation plan of the machine will be described. Here, the operation plan is a plan that indicates the route along which the agricultural machine will be moved.

[0010] Note that tractors, combine harvesters, and rice transplanters are examples of agricultural machinery, and other agricultural machinery may also include, for example, agricultural robots (such as mowing robots and harvesting robots). Furthermore, agricultural machinery does not necessarily need to be capable of running; it may be, for example, an agricultural machine capable of flying, such as an agricultural drone. Furthermore, the embodiments described below can be similarly applied to other moving objects that move according to an operation plan in places where lanes, drivable areas, and the like are not clearly defined, in addition to agricultural machinery.

[0011] <Travel route of agricultural machinery and predicted destination using conventional technology> Generally, agricultural machinery moves according to an operation plan that takes into account planting points (or harvesting points, etc.) within a field. For example, consider a case where the planting points exist in a grid pattern within a field, and the agricultural machinery departs from a certain starting point, plants at each planting point, and then returns to the original starting point. In this case, the operation plan of the agricultural machinery may represent a route that passes through planting points 1001 to 1005 in order, then changes direction, then passes through planting points 1006 to 1010 in order, changes direction again, passes through planting points 1011 to 1015 in order, leaves the field, and finally returns to the starting point, as shown in FIG. 1.

[0012] In this way, when agricultural machinery is moved according to an operation plan, the movement route of the agricultural machinery generally includes direction changes (points indicated by reference numerals 2001 to 2004 on the movement route).

[0013] On the other hand, conventional technology predicts the destination of agricultural machinery using only its movement history. As a result, it is unable to handle sudden changes in direction (in other words, sudden changes in the speed vector) of agricultural machinery, resulting in the problem that the prediction of the destination may be inaccurate. Furthermore, unlike roads where lanes and drivable areas are clearly defined, there are no lanes in fields and the drivable area is not clear. Therefore, even if the destination is predicted using map information, camera images, etc. as an auxiliary tool, the same problem may occur.

[0014] For example, when predicting the destination immediately before a direction change indicated by reference numeral 2001, in the conventional technology, a predicted region 3001 is predicted as the region where the destination exists a certain time Δt from now, using a current velocity vector calculated from current and past position information (movement history). Note that while this conventional technology shows a case where the destination is predicted as a region, it may also be predicted as a point. However, because agricultural machinery changes direction (turns around), this predicted region 3001 does not predict the actual destination of the agricultural machinery.

[0015] Thus, for example, when targeting agricultural machinery traveling in a field, the prior art prediction of destinations uses only the movement history, and therefore the prediction may be incorrect due to the agricultural machinery changing direction, etc. For this reason, it may not be possible to estimate the network quality at the actual destination of the agricultural machinery, and as a result, it may not be possible to realize speed control of the agricultural machinery.

[0016] An example of a technology for estimating network quality is the "multi-wireless quality prediction technology" described in Non-Patent Document 1. Furthermore, an example of a technology for automatically slowing down or stopping agricultural machinery when the network quality at the destination is poor is the "network cooperative device control technology" described in Non-Patent Document 1. Furthermore, an example of a technology for analyzing video from a camera mounted on agricultural machinery on the edge / cloud side and notifying a remote control terminal or the like of any danger is the "data stream assist technology that enables the simultaneous use of real-time video for multiple purposes such as remote monitoring and image analysis while reducing network load by duplicating video at the packet level at a monitoring station with low latency" described in Non-Patent Document 1.

[0017] To solve the problems with the conventional technology described above, the autonomous driving system 1 described below predicts the destination of the agricultural machinery taking into account its operation plan. This makes it possible to more accurately predict the actual destination of the agricultural machinery, which in turn makes it possible to estimate the network quality at the actual destination of the agricultural machinery and control the speed of the agricultural machinery using that network quality, thereby achieving safer and higher quality autonomous driving.

[0018] <Example of overall configuration of Autonomous Driving System 1> FIG. 3 shows an example of the overall configuration of an automated driving system 1 according to this embodiment. As shown in FIG. 3, the automated driving system 1 according to this embodiment includes one or more agricultural machines 10, a position information providing server 20, a position information database 30, an operation plan database 40, an auxiliary information database 50, a remote control terminal 60, a NW quality prediction server 70, and an automatic control server 80. The agricultural machines 10, the position information providing server 20, the remote control terminal 60, the NW quality prediction server 70, and the automatic control server 80 are communicatively connected to each other via a communication network 90, such as the Internet. The position information providing server 20 functions as a positioning network services (PNSS) for providing the position information (past, present, and future position information) of the agricultural machines 10 to other devices, systems, equipment, etc. The position information database 30, the operation plan database 40, and the auxiliary information database 50 function as an information distribution infrastructure for managing and providing various information.

[0019] The agricultural machine 10 is an agricultural machine that automatically operates (including agricultural operations such as plowing, planting, harvesting, and the like, in addition to traveling, etc.) according to a given operation plan. The agricultural machine 10 is equipped with at least a GNSS (Global Navigation Satellite System) receiver (GNSS receiver) and a camera (photography device or imaging device). The agricultural machine 10 can receive signals (GNSS signals) from GNSS satellites using the GNSS receiver. The agricultural machine 10 can also capture images or videos of its surroundings using the camera.

[0020] The agricultural machine 10 may be equipped with various sensors in addition to the GNSS receiver and the camera, and may acquire or measure various pieces of information using these sensors. Examples of such sensors include an acceleration sensor (including a three-axis acceleration sensor), a gyro sensor (including a three-axis gyro sensor), and an inertial measurement unit (IMU). Hereinafter, information acquired or measured by various sensors including a camera will be referred to as sensor information. The sensor information includes at least images or videos captured by a camera (hereinafter also referred to as camera images or camera videos).

[0021] The location information providing server 20 is a general-purpose server or the like that measures the location information of the agricultural machine 10 using GNSS signals and sensor information received from the agricultural machine 10, and predicts future location information of the agricultural machine 10 in consideration of an operation plan for the agricultural machine 10. In addition, in response to a request from the NW quality prediction server 70, the location information providing server 20 provides location information related to the request.

[0022] The position information database 30 is a database server that stores data (hereinafter also referred to as position information data) including position information measured or predicted by the position information providing server 20. Here, the position information database 30 stores position information data in the format of (agricultural machine ID, time, position information), for example. The agricultural machine ID is identification information that identifies the agricultural machine 10. The time is information indicating the date and time when the position information was measured, or information indicating the date and time (future date and time) when the position information is predicted. Note that the position information data may further include, for example, information indicating whether the position information is measured or predicted.

[0023] The operation plan database 40 is a database server that stores data including operation plans for the agricultural machines 10 (hereinafter also referred to as operation plan data). Here, the operation plan database 40 stores operation plan data in the format of (agricultural machine ID, operation plan), for example.

[0024] The auxiliary information database 50 is a database server that stores data including auxiliary information used for positioning and prediction of location information (hereinafter also referred to as auxiliary information data). The auxiliary information may be any information used auxiliary for positioning or prediction of location information, such as map information (2D map information, 3D map information, 4D map information, etc.), surrounding information (weather information, traffic information, accident information, construction information, etc.), calendar information (date, season, time, etc.), and some event information. In addition to these, the auxiliary information may also be information on crops that are scheduled to be planted or are being grown in the field (crop growth status, planting intervals, etc.), information on the characteristics and model of the agricultural machine 10, etc. The auxiliary information database 50 stores auxiliary information data in various formats depending on the type or category of auxiliary information.

[0025] The remote control terminal 60 is a terminal of any type used by a person (remote monitor) who monitors camera images (or camera footage) captured by a camera equipped in the agricultural machine 10 and controls the operation of the agricultural machine 10 as necessary. The remote control terminal 60 is installed, for example, in a facility such as a remote control room for remotely monitoring and controlling the automatic operation of the agricultural machine 10. If any danger (contact, rear-end collision, etc.) exists in the agricultural machine 10, a warning or the like is notified to the remote control terminal 60, for example, by using the conventional technology described in Non-Patent Document 1. This warning notification function may be possessed by the position information providing server 20 or may be possessed by a server or the like different from the position information providing server 20. The remote control terminal 60 may be, for example, a personal computer (PC), a smartphone, a tablet terminal, a wearable device, or the like.

[0026] The NW quality prediction server 70 uses the location information provided by the location information providing server 20 to predict the NW quality at the location indicated by the location information using existing NW quality estimation technology (for example, the "multi-wireless quality prediction technology" described in Non-Patent Document 1).

[0027] The automatic control server 80 uses the NW quality predicted by the NW quality prediction server 70 to control the speed of the corresponding agricultural machine 10 using existing speed control technology (for example, the "network cooperative device control technology" described in Non-Patent Document 1). With such speed control technology, for example, when the network quality deteriorates to a level where camera images (or camera videos) captured by a camera equipped in the agricultural machine 10 cannot be transmitted, the agricultural machine 10 can be automatically and safely stopped. As a result, even when the network quality is poor and a remote monitor cannot monitor camera images, etc., the agricultural machine 10 is automatically stopped, thereby ensuring its safety.

[0028] 1 is an example and is not limited to this. For example, if a positioning method (e.g., RTK (Real Time Kinematic) positioning, etc.) that requires a reference station is used to measure the position information of the agricultural machine 10, a reference station database may be present that stores data including information about the reference station (e.g., the range of positions within which the reference station is the nearest reference station). In addition to the NW quality prediction server 70, there may also be a server or the like that performs some kind of processing or service using the position information provided by the position information providing server 20.

[0029] <Example of functional configuration of agricultural machine 10 and location information providing server 20> An example of the functional configuration of the agricultural machine 10 and the position information providing server 20 according to this embodiment will be described below.

[0030] ≪Agricultural machinery 10≫ An example of the functional configuration of the agricultural machine 10 according to this embodiment is shown in Fig. 4. As shown in Fig. 4, the agricultural machine 10 according to this embodiment has a GNSS signal receiving unit 101, a sensor information acquiring unit 102, an operation control unit 103, and a communication unit 104. Each of these functional units is realized by, for example, one or more programs installed in the agricultural machine 10, a calculation device such as a CPU (Central Processing Unit) that executes processing in accordance with those programs, a GNSS receiver, various sensors, an interface device for connecting to the communication network 90, and the like.

[0031] The GNSS signal receiving unit 101 receives GNSS signals from GNSS satellites. The sensor information acquiring unit 102 acquires sensor information (including at least camera images or camera videos) from various sensors including at least a camera. The operation control unit 103 controls the operation of the agricultural machine 10 in accordance with a given operation plan. The operation plan is provided, for example, from a remote control terminal 60. The communication unit 104 transmits the given operation plan to the position information providing server 20, and also transmits the GNSS signals received by the GNSS signal receiving unit 101 and the sensor information acquired by the sensor information acquiring unit 102 to the position information providing server 20. At this time, the communication unit 104 also transmits its own agricultural machine ID, etc. to the position information providing server 20.

[0032] The GNSS signal receiving unit 101 receives GNSS signals at a predetermined signal reception period. Similarly, the sensor information acquiring unit 102 acquires sensor information from the corresponding sensor at a predetermined sensing period.

[0033] In addition, the driving control unit 103 may, for example, detect obstacles in front of (or around) the agricultural machine 10 and perform control to avoid the obstacle or slow down if the obstacle is a moving object (for example, another agricultural machine 10).

[0034] <Location information providing server 20> An example of the functional configuration of location information providing server 20 according to this embodiment is shown in Fig. 5. As shown in Fig. 5, location information providing server 20 according to this embodiment includes communication unit 201, positioning calculation unit 202, location prediction unit 203, and intermediation unit 204. Each of these functional units is realized by, for example, one or more programs installed in location information providing server 20, a calculation device such as a CPU that executes processing in accordance with those programs, an interface device for connecting to communication network 90, or the like.

[0035] The communication unit 201 receives an operation plan from the agricultural machine 10, as well as GNSS signals and sensor information. The positioning calculation unit 202 uses the GNSS signals (or both the GNSS signals and the sensor information) received by the communication unit 201 to determine the position information of the agricultural machine 10 that is the sender of the GNSS signals. The position prediction unit 203 predicts future position information of the agricultural machine 10 using the operation plan of the agricultural machine 10 and the movement history of the agricultural machine 10 (i.e., current and past position information). When position information is requested from the NW quality prediction server 70, the intermediary unit 204 determines whether or not position information data including the position information related to the request exists in the position information database 30.

[0036] <Storage process for operation plan data and location information data> The process of storing operation plan data in the operation plan database 40 and storing position information data in the position information database 30 will be described below with reference to Fig. 6. Note that the following steps S103 to S105 are repeatedly executed each time a GNSS signal and sensor information are transmitted from each agricultural machine 10.

[0037] The communication unit 201 of the location information providing server 20 receives the agricultural machine ID and the operation plan from the agricultural machine 10 (step S101). When an operation plan is provided from the remote control terminal 60, for example, each agricultural machine 10 sets the operation plan for itself and transmits the operation plan and its own agricultural machine ID to the location information providing server 20.

[0038] The communication unit 201 of the position information providing server 20 stores the operation plan data including the agricultural machine ID and the operation plan received in step S101 above in the operation plan database 40 (step S102). As a result, the operation plan of the agricultural machine 10 is managed in the operation plan database 40.

[0039] The operation plan may be changed or updated. In this case, the agricultural machine 10 may transmit its own agricultural machine ID and the changed or updated operation plan to the location information providing server 20. As a result, the operation plan of the operation plan data including the agricultural machine ID among the operation plan data stored in the operation plan database 40 is updated to the changed or updated operation plan. Here, the operation plan may be changed or updated based on various factors. For example, the operation plan may be changed or updated based on factors such as weather, the results of the previous automated driving according to the operation plan, the results of the automated driving of other agricultural machines 10, the results of the automated driving of multiple agricultural machines 10, etc. To give a specific example, the operation plan may be changed or updated when the weather changes (including when the temperature changes, etc.), or when the results of the previous automated driving according to the operation plan were poor based on some evaluation index (for example, when the fuel efficiency or travel route of the agricultural machine 10 was inefficient, etc.). Alternatively, for example, if the automated driving results of another agricultural machine 10 are poor based on some evaluation index, a similar operation plan may be changed or updated, or if the results are poor based on an evaluation index representing the overall efficiency, safety, etc. of multiple agricultural machines 10, the operation plan may be changed or updated. However, these are merely examples, and the operation plan may also be changed or updated according to the value of some evaluation index representing the convenience, efficiency, economy, safety, etc. of the operation plan of one or more agricultural machines 10. Furthermore, the operation plan may be changed or updated based on not only one element but also a combination or weighting of multiple elements, or the operation plan may be changed or updated by prioritizing the elements. Note that changing or updating the operation plan may also include, for example, restoring the operation plan to its original state after changing or updating it.

[0040] The communication unit 201 of the position information providing server 20 receives the agricultural machine ID, the GNSS signal, and the sensor information from the agricultural machine 10 (step S103).

[0041] Next, the positioning calculation unit 202 of the position information providing server 20 uses the GNSS signal (or both the GNSS signal and the sensor information) received in step S103 to determine the current position information of the agricultural machine 10 identified by the agricultural machine ID (step S104). The positioning calculation unit 202 may determine the current position information of the agricultural machine 10 using any positioning method (e.g., a known positioning method such as code positioning or RTK positioning). At this time, the positioning calculation unit 202 may achieve higher accuracy of positioning by using auxiliary information data stored in the auxiliary information database 50 or by using sensor information. Examples of techniques for achieving such higher accuracy of positioning include matching with map information, estimating position information using spatial information from a 3D map or a 4D map, image positioning by analyzing camera images or camera footage included in the sensor information, dead reckoning using acceleration values ​​and inertial measurement values ​​included in the sensor information, and estimating position information using radio wave intensity, beacons, etc.

[0042] Then, the positioning calculation unit 202 of the position information providing server 20 stores the position information data (agricultural machine ID, time, position information) including the agricultural machine ID, the time when the positioning was performed in the above step S104, and the position information that is the positioning result, in the position information database 30 (step S105). As a result, the position information data including the position information of the agricultural machine 10 identified by the agricultural machine ID at the current time is stored in the position information database 30.

[0043] <Location information prediction processing> The process of predicting future position information of an agricultural machine 10 identified by a certain agricultural machine ID will be described below with reference to Fig. 7. Note that the following steps S201 to S202 are repeatedly executed in the background for the agricultural machine ID at predetermined intervals, for example.

[0044] The position prediction unit 203 of the position information providing server 20 predicts position information for a predetermined future time (for example, time T+Δt, which is Δt seconds from the current time T) using operation plan data including the agricultural machine ID and position information data including the agricultural machine ID (step S201). That is, the position prediction unit 203 predicts future position information using an operation plan for the agricultural machine 10 of the agricultural machine ID and position information (current and past position information) of the agricultural machine ID, by any prediction method, while also taking into account the movement route when the agricultural machine 10 moved according to the operation plan. At this time, the position prediction unit 203 may predict future position information using various information other than the operation plan and the current and past position information. For example, the position prediction unit 203 may predict future position information by further using at least one of map information (2D map information, 3D map information, 4D map information, etc.), surrounding information (weather information, traffic information, accident information, construction information, etc.), calendar information (date, season, time, etc.), event information, crop information (crop growth status, planting intervals, etc.), and information regarding the characteristics and model of the agricultural machinery 10.

[0045] Any prediction method can be used as long as it is a method that can take into account the movement path of the agricultural machine 10 when it moves according to the operation plan. For example, a simple method is to calculate a velocity vector at the current time from the movement history (current and past position information) of the agricultural machine 10, and then predict position information Δt seconds from the value of the component of this velocity vector along the movement path.

[0046] In this way, in the above step S201, future location information is predicted using not only the movement history of the agricultural machine 10 but also the operation plan of the agricultural machine 10. This makes it possible to predict location information with higher accuracy by taking the operation plan into consideration. Note that, for example, when the operation plan is changed or updated, the operation plan included in the operation plan data is also changed or updated without delay, and therefore, when predicting future location information in the above step S201, the changed or updated operation plan is used.

[0047] Then, the position prediction unit 203 of the position information providing server 20 stores the position information data (agricultural machine ID, time, position information) including the agricultural machine ID, the time that was the target of prediction in the above step S201, and the position information that is the prediction result in the position information database 30 (step S202). As a result, the position information data including (the predicted value of) the position information of the agricultural machine 10 identified by the agricultural machine ID at a future time (for example, time T+Δt that is Δt seconds after the current time T) is stored in the position information database 30.

[0048] <Location information provision processing> The process of providing location information related to a request from the NW quality prediction server 70 in response to the request will be described below with reference to Fig. 8. In the following, as an example, the NW quality prediction server 70 requests future location information (for example, location information for a time Δt seconds from the current time) of an agricultural machine 10 identified by a certain agricultural machine ID. However, this is just an example, and the NW quality prediction server 70 may request current or past location information. Note that the following steps S301 to S306 are executed when a request to obtain location information is sent from the NW quality prediction server 70 to the location information providing server 20.

[0049] The communication unit 201 of the position information providing server 20 receives a request to acquire future position information of the agricultural machine 10 identified by the agricultural machine ID (step S301).

[0050] Next, the intermediary unit 204 of the location information providing server 20 determines whether the location information related to the acquisition request received in the above step S301 (i.e., the location information for the agricultural machine 10 at time T+Δt) exists in the location information database 30 (step S302).

[0051] If it is determined in step S302 above that the location information related to the acquisition request exists, the location information providing server 20 proceeds to step S305. On the other hand, if it is not determined in step S302 above that the location information related to the acquisition request exists, the location prediction unit 203 of the location information providing server 20 predicts the location information at time T+Δt of the agricultural machine 10 identified by the agricultural machine ID, using the operation plan data including the agricultural machine ID and the location information data including the agricultural machine ID, as in step S201 in Fig. 7 (step S303).

[0052] Next, the location prediction unit 203 of the location information providing server 20 stores location information data including the agricultural machinery ID, the time T+Δt predicted in the above step S303, and the location information that is the prediction result in the location information database 30, similar to step S202 in Figure 7 (step S304).

[0053] The communication unit 201 of the position information providing server 20 acquires the position information related to the acquisition request (that is, the position information at time T+Δt related to the agricultural machine 10) from the position information database 30 (step S305).

[0054] Then, the communication unit 201 of the position information providing server 20 returns the position information acquired in the above step S305 to the NW quality prediction server 70, which is the sender of the acquisition request (step S306). As a result, the NW quality prediction server 70 can predict the NW quality of the position (or the surrounding area may be included) indicated by the position information (position information at time T+Δt related to the agricultural machine 10) and transmit this NW quality to the automatic control server 80. Thereafter, the automatic control server 80 can use the NW quality received from the NW quality prediction server 70 to control the speed of the agricultural machine 10 by speed control technology.

[0055] <Modification> Variation 1 In the above embodiment, the NW quality prediction server 70 is assumed to be the recipient of the location information (future / present / past location information), but the present invention is not limited to this. Any server that receives location information from the location information providing server 20 and performs some kind of processing or service can be the target.

[0056] Variation 2 In the above embodiment, future location information is predicted in the background (FIG. 7), but this is not limited to this. For example, prediction may not be performed in the background, and location information may be predicted each time future location information is requested from the NW quality prediction server 70.

[0057] Variation 3 When predicting future location information in step S201 of Fig. 7 or step S303 of Fig. 8, a travel route that avoids construction sites or accident locations may be created or predicted based on construction information, accident information, etc., and future location information may be predicted taking that travel route into consideration. At this time, the travel route that avoids construction sites or accident locations may be fed back to the remote control terminal 60.

[0058] Variation 4 7 or step S303 in Fig. 8, it is possible to determine whether or not an obstacle exists on the movement path of the agricultural machine 10 when it moves according to the operation plan, based on camera images or camera videos, and if an obstacle exists, create or predict a movement path that avoids the obstacle, and then predict future position information taking that movement path into consideration. At this time, the movement path that avoids the obstacle may be fed back to the remote control terminal 60.

[0059] Variation 5 When creating or predicting a travel path to avoid an obstacle in the above-mentioned variant example 4, if some obstacle has been avoided in the past by remote control from a remote monitor, the travel path to avoid the obstacle may be created or predicted using steering information, etc. at that time.

[0060] Variation 6 When predicting the future position information of a certain agricultural machine 10 in step S201 of Figure 7 or step S303 of Figure 8, the position information database 30 may be referenced to simultaneously estimate the future position information of other agricultural machines 10, and if there is a possibility that other agricultural machines 10 may enter the movement path of the certain agricultural machine 10, the future position information may be predicted taking into account the slowdown of the speed of the certain agricultural machine 10 (or any other avoidance action).

[0061] Variation 7 A server or system may be present that changes the harvesting route (or fertilization route) in real time based on the growth information of the crops in the field, and the operation plan may be changed or updated in real time based on this harvesting route (or fertilization route). This makes it possible to predict future position information of the agricultural machine 10 using the operation plan that has been changed or updated in real time.

[0062] <Summary> As described above, in the autonomous driving system 1 according to this embodiment, when estimating future position information of the agricultural machine 10 that is the target of autonomous driving, the future position information is estimated using not only the movement history of the agricultural machine 10 but also the operation plan of the agricultural machine 10. This makes it possible to estimate future position information of the agricultural machine 10 with higher accuracy than conventional techniques. Therefore, it becomes possible to provide highly accurate position information to various servers, devices, equipment, services, etc. that support or realize the autonomous driving of the agricultural machine 10, for example, and as a result, it becomes possible to realize safer and higher quality autonomous driving.

[0063] The present invention is not limited to the above-described specifically disclosed embodiments, and various modifications, changes, and combinations with known technologies are possible without departing from the scope of the claims. [Explanation of symbols]

[0064] 1. Autonomous driving system 10 Agricultural machinery 20 Location information server 30 Location Database 40 Operation plan database 50 Auxiliary Information Database 60 Remote Control Terminal 70 Network quality prediction server 80 Automatic Control Server 90 Communication Network 101 GNSS signal receiver 102 Sensor information acquisition unit 103 Operation control unit 104 Communications Department 201 Communications Department 202 Positioning calculation unit 203 Position Prediction Unit 204 Intermediary Department

Claims

1. A location information providing device connected to a mobile object having at least a GNSS receiver via a communication network, a positioning unit configured to measure a current position of the moving object based on the GNSS signal received by the GNSS receiver; a prediction unit configured to predict a future position of the moving object based on a movement history of the moving object and an operation plan that indicates a route along which the moving object will move to a harvesting point or a fertilization point within a farm field; a providing unit configured to provide the requested location information indicating the past, present, or future location of the mobile object to the server when the location information is requested from the server that controls the travel and agricultural work operation of the mobile object; and The operation plan is changed or updated in real time based on growth information of crops to be harvested or fertilized in the field.

2. The providing unit The location information providing device according to claim 1 , configured to provide the requested location information to a server that executes processing related to automatic driving of the mobile object in response to the request from the server.

3. The prediction unit 3. The location information providing device according to claim 1 or 2, configured to predict the future location of the mobile body further based on at least one of 2D map information, 3D map information, 4D map information, weather information, traffic information, accident information, construction information, calendar information, event information, crop information in a field through which the mobile body moves, and information regarding the characteristics or model of the mobile body.

4. The moving object further includes an imaging device, The prediction unit determining whether or not an obstacle is present when the moving object moves according to the operation plan based on the image captured by the imaging device; If it is determined that the obstacle exists, creating or predicting a travel path that avoids the obstacle; The position information providing device according to claim 1 , configured to predict a future position of the mobile object based on the movement history of the mobile object and the created or predicted movement route.

5. The prediction unit 4. The position information providing device according to claim 3, wherein, when remote control to avoid an obstacle has been performed on the moving body in the past, the device is configured to predict the future position of the moving body based on predetermined information including steering information at the time of the remote control.

6. When there is a possibility of a collision between the moving body and another moving body, avoidance control including deceleration control is performed to avoid the collision; The prediction unit The position information providing device according to claim 1 , further configured to predict a future position of the moving body based on the avoidance control when there is a possibility of a collision with the other moving body.

7. A location information providing device connected to a mobile object having at least a GNSS receiver via a communication network, a positioning procedure for determining a current position of the moving object based on the GNSS signal received by the GNSS receiver; a prediction step of predicting a future position of the moving object based on a movement history of the moving object and an operation plan that indicates a route along which the moving object will move to a harvesting point or a fertilization point within a farm field; a provision step of providing the requested location information indicating the past, present, or future location of the mobile object to the server when the location information is requested from the server that controls the travel and agricultural work operation of the mobile object; Run A location information providing method, wherein the operation plan is changed or updated in real time based on growth information of crops to be harvested or fertilized in the field.

8. A location information providing device connected to a mobile body having at least a GNSS receiver via a communication network, a positioning procedure for determining a current position of the moving object based on the GNSS signal received by the GNSS receiver; a prediction step of predicting a future position of the moving object based on a movement history of the moving object and an operation plan that indicates a route along which the moving object will move to a harvesting point or a fertilization point within a farm field; a provision step of providing the requested location information indicating the past, present, or future location of the mobile object to the server when the location information is requested from the server that controls the travel and agricultural work operation of the mobile object; Execute The operation plan is changed or updated in real time based on growth information of crops to be harvested or fertilized in the field.

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