System, out-of-vehicle system, and vehicle

Abstract

A system (1) comprises an out-of-vehicle system (3) and a vehicle (5). The out-of-vehicle system comprises a model generating unit (7) and an out-of-vehicle system-side storage unit (9). The vehicle comprises: a model downloading unit (21); a download possibility determining unit (23) that determines whether download data (13) can be downloaded; and a download processing unit (25) that downloads the download data from the out-of-vehicle system to the vehicle if it is determined that the download data can be downloaded.

Description

System, off-vehicle system, and vehicle CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This international application claims priority based on Japanese Patent Application No. 2024-012932, filed with the Japan Patent Office on January 31, 2024, the entire contents of which are incorporated herein by reference.

[0002] The present disclosure relates to a system, an off-vehicle system, and a vehicle.

[0003] Patent Literature 1 discloses a system including a cloud and a vehicle. Large amounts of data may be downloaded from the cloud to the vehicle. Examples of such large amounts of data include model data. The model data is used to update the models of apps used in the vehicle.

[0004] JP 2023-84379 A

[0005] As a result of detailed investigation by the inventors, the following problem was found: When downloading large amounts of data from the cloud to a vehicle, the download may fail. If the download fails, problems such as the inability to update the model may arise.

[0006] In one aspect of the present disclosure, it is preferable to provide a system, an off-vehicle system, and a vehicle that can suppress download failures.

[0007] One aspect of the present disclosure is a system including an off-vehicle system and a vehicle, wherein the off-vehicle system includes a model generation unit configured to generate a model that determines whether download data can be downloaded from the off-vehicle system to the vehicle, and an off-vehicle system-side storage unit configured to store the download data.

[0008] The vehicle includes a model download unit configured to download the model from the extra-vehicle system to the vehicle, a download feasibility determination unit configured to determine whether the download data can be downloaded based on a determination result when input data representing conditions that affect the download of the download data is input to the model downloaded by the model download unit, and a download processing unit configured to download the download data from the extra-vehicle system to the vehicle when the download feasibility determination unit determines that the download data can be downloaded.

[0009] A system that is one aspect of the present disclosure can reduce download failures.

[0010] Another aspect of the present disclosure is an off-vehicle system including: a model generation unit configured to generate a model that determines whether download data can be downloaded from the off-vehicle system to a vehicle and provide the model to the vehicle; and an off-vehicle system side memory unit configured to store the download data and provide the model to the vehicle.

[0011] The off-vehicle system, which is another aspect of the present disclosure, can suppress download failures.

[0012] Another aspect of the present disclosure is a vehicle including: a model download unit configured to download, from an extra-vehicle system, a model that determines whether download data can be downloaded from the extra-vehicle system to a vehicle; a download feasibility determination unit configured to determine whether the download data can be downloaded based on a determination result when input data representing conditions that affect the download of the download data is input to the model downloaded by the model download unit; and a download processing unit configured to download the download data from the extra-vehicle system to the vehicle when the download feasibility determination unit determines that the download data can be downloaded.

[0013] In another aspect of the present disclosure, the vehicle can suppress download failures.

[0014] It is a block diagram showing the configuration of the system. It is a flowchart showing the process from model generation to setting. It is a flowchart showing the download process of download data.

[0015] An exemplary embodiment of the present disclosure will be described with reference to the drawings. First Embodiment 1. Configuration of System 1 (1-1) Overall Configuration of System 1 The configuration of System 1 will be described with reference to FIG. 1. System 1 includes a cloud 3 and a vehicle 5. There may be one or more vehicles 5. The cloud 3 corresponds to an external vehicle system.

[0016] (1-2) Configuration of Cloud 3 The cloud 3 includes a model generation unit 7 and a cloud-side storage unit 9. The cloud-side storage unit 9 corresponds to the external-vehicle system storage unit. The model generation unit 7 generates a model 11. The model 11 is a model that determines whether or not download data 13 can be downloaded from the cloud 3 to the vehicle 5. The download data 13 is, for example, large-scale data. The model 11 generated by the model generation unit 7 is provided to the vehicle 5.

[0017] When input data 12 described below is input, model 11 calculates the probability of completing the download of download data 13 (hereinafter referred to as completion probability). Model 11 outputs download feasibility determination result 14 based on the calculated completion probability. There are two types of download feasibility determination result 14: download possible and download impossible. Model 11 outputs download possible when the calculated completion probability is equal to or greater than a threshold. Model 11 outputs download impossible when the calculated completion probability is less than the threshold.

[0018] The model generation unit 7 generates the model 11 using, for example, vehicle data 15 and feedback data 17. The vehicle data 15 is information that the cloud 3 repeatedly acquires from the vehicle 5. The vehicle data 15 includes, for example, the model and grade of the vehicle 5, the total mileage of the vehicle 5, the driving history of the vehicle 5, the specifications of each ECU installed in the vehicle 5, and the operation history and resource usage history of each ECU installed in the vehicle 5.

[0019] The feedback data 17 is information that is generated by the vehicle 5 and uploaded to the cloud 3. The contents of the feedback data 17 will be described later.

[0020] The cloud-side storage unit 9 stores download data 13 and download data information 19. The download data information 19 is information related to the download data 13. The download data information 19 includes, for example, the data format of the download data 13 and the size of the download data 13. Examples of the data format of the download data 13 include JavaScript Object Notation (JSON) and binary.

[0021] The download data information 19 also includes, for example, the access destination when downloading the download data 13. The download data information 19 also includes, for example, information on the storage destination of the download data 13 after it has been downloaded.

[0022] The download data information 19 also includes instruction necessity information. The instruction necessity information is information that specifies whether a download instruction is necessary when downloading the download data 13. The download instruction is an instruction that the user of the vehicle 5 issues to the instruction receiving unit 35, which will be described later. The download instruction is an instruction to download the download data 13 from the cloud 3.

[0023] (1-3) Configuration of vehicle 5 The vehicle 5 includes a model download unit 21, a download possibility determination unit 23, a download processing unit 25, a feedback unit 27, a route suggestion unit 31, a download impossible processing unit 33, and an instruction receiving unit 35.

[0024] The model download unit 21 downloads the model 11 from the cloud 3 to the vehicle 5. The download permission determination unit 23 inputs input data 12 to the model 11 downloaded by the model download unit 21. The model 11 outputs a download permission determination result 14 in response to the input of the input data 12. The download permission determination unit 23 determines whether or not the download data 13 can be downloaded in response to the download permission determination result 14.

[0025] If the download permission determination result 14 indicates that downloading is possible, the download permission determination unit 23 determines that downloading is possible. If the download permission determination result 14 indicates that downloading is not possible, the download permission determination unit 23 determines that downloading is not possible.

[0026] The input data 12 is information that indicates conditions that affect the download of the download data 13. The input data 12 includes, for example, planned driving route data 41, vehicle state data 43, and download data information 19.

[0027] The planned driving route data 41 includes, for example, information on a planned driving route of the vehicle 5. The planned driving route data 41 also includes, for example, information on a plurality of candidate driving routes. The planned driving route is selected from, for example, a plurality of candidate driving routes. This will be described in detail later.

[0028] The planned driving route data 41 also includes, for example, a plurality of pieces of spot information that indicate spots near the planned driving route. The spot information is, for example, information that indicates the location of the spot. The planned driving route data 41 also includes, for example, estimated download information for the planned driving route. The estimated download information for the planned driving route is information on the amount of download data and the download speed for the planned driving route.

[0029] The planned driving route data 41 also includes, for example, estimated download information for each of a plurality of candidate driving routes. The estimated download information for a candidate driving route is information on the amount of download data and the download speed for the candidate driving route.

[0030] The planned driving route data 41 also includes, for example, estimated download information for each of a plurality of spots near the planned driving route. The estimated download information for a spot is information on the amount of download data and the download speed at the spot.

[0031] The vehicle status data 43 includes, for example, the model and grade of the vehicle 5, location information of the vehicle 5, network strength of the vehicle 5, specifications of each ECU installed in the vehicle 5, and operation history and resource usage history of each ECU installed in the vehicle 5.

[0032] The relationship between the content of the input data 12 and the download permission determination result 14 output by the model 11 when the input data 12 is input is, for example, as follows:

[0033] The planned driving route data 41 includes the download data amount and download speed for the planned driving route. The larger the download data amount and download speed for the planned driving route, the more likely the download possibility determination result 14 will be download possible.

[0034] The vehicle state data 43 includes the network strength of the vehicle 5. The higher the network strength of the vehicle 5, the more likely the download availability determination result 14 will indicate that download is available.

[0035] The vehicle state data 43 includes the specifications of each ECU installed in the vehicle 5. The higher the specifications of each ECU installed in the vehicle 5, the more likely the download permission determination result 14 will be "download permission."

[0036] The vehicle state data 43 includes the operating status of each ECU mounted on the vehicle 5. The lower the operating rate indicated by the operating status, the more likely the download availability determination result 14 will indicate that download is available.

[0037] The download data information 19 includes the size of the download data 13. The smaller the size of the download data 13, the more likely the download permission determination result 14 will be "downloadable."

[0038] If the download permission determination unit 23 determines that the download data 13 can be downloaded, the download processing unit 25 downloads the download data 13 from the cloud 3 to the vehicle 5 .

[0039] The feedback unit 27 generates feedback data 17 and uploads the feedback data 17 to the cloud 3. The feedback data 17 includes, for example, a download result 45 by the download processing unit 25, the input data 12, the download possibility determination result 14, and the ID of the model 11. The download result 45 is information indicating whether the download was successful or unsuccessful.

[0040] As will be described later, when the download data 13 is downloaded in response to a download instruction, the feedback data 17 further includes information indicating that a download instruction has been issued.

[0041] The route proposing unit 31 calculates the completion probability for each of a plurality of candidate driving routes using the model 11. The route proposing unit 31 proposes the candidate driving route with the highest completion probability to the user of the vehicle 5 as the planned driving route of the vehicle 5. The proposal can be made, for example, by using an image, a sound, or the like. The user of the vehicle 5 can select the proposed candidate driving route as the planned driving route.

[0042] A plurality of candidate driving routes are included in planned driving route data 41. The route proposing unit 31 inputs input data 12 corresponding to the candidate driving routes into the model 11, thereby acquiring the completion probability of the candidate driving routes.

[0043] The download-impossible processing unit 33 executes a process for when download is impossible when the download possibility determination unit 23 determines that download of the download data 13 is impossible. Examples of the process for when download is impossible include the following first process and second process. (First process) The download-impossible processing unit 33 notifies the user of the vehicle 5 of spots located around the planned route of the vehicle 5 and the estimated time required to download the download data 13 at each spot.

[0044] Spots in the vicinity of the planned driving route are included in the planned driving route data 41. The download-unavailable time processing unit 33 calculates a predicted time using estimated download information for the spots included in the planned driving route data 41. The download-unavailable time processing unit 33 notifies the user of the vehicle 5 of the spots and the predicted time, for example, using an image or audio. (Second Process) The download-unavailable time processing unit 33 predicts a future time when downloading of the download data 13 will be possible based on the driving history of the vehicle 5, the planned driving route of the vehicle 5, and the current state of the vehicle 5. The download-unavailable time processing unit 33 notifies the user of the vehicle 5 of the predicted time.

[0045] The current state of the vehicle 5 is included in the vehicle state data 43. The download impossible time processing unit 33 notifies the user of the vehicle 5 of the predicted timing using, for example, an image or sound.

[0046] At the predicted timing, the download possibility determination unit 23 again determines whether the download data 13 can be downloaded. If the result of the determination is that the download is possible, the download processing unit 25 downloads the download data 13 from the cloud 3.

[0047] The download-disabled time processing unit 33 may execute either the first process or the second process, or may execute both of them. The download-disabled time processing unit 33 corresponds to the spot notification unit, the timing prediction unit, and the timing notification unit.

[0048] The instruction receiving unit 35 receives instructions from the user of the vehicle 5. The instruction receiving unit 35 includes, for example, a touch panel, buttons, switches, a keyboard, a voice input device, etc. The instructions from the user of the vehicle 5 include a download instruction.

[0049] 2. Processing from generation to setting of model 11 Processing from generation to setting of model 11 will be described with reference to Fig. 2. Of this processing, steps 1 and 2 are executed by the cloud 3. Steps 3 and 4 are executed by the vehicle 5.

[0050] In step 1, the model generation unit 7 acquires the vehicle data 15 and the feedback data 17.

[0051] In step 2, the model generation unit 7 generates a model 11 using the vehicle data 15 and feedback data 17 acquired in step 1.

[0052] For example, the model generation unit 7 can generate the model 11 by the following methods (a) and (b): In either case, the model generation unit 7 assigns a model ID to the generated model 11.

[0053] (a) The model generation unit 7 generates the model 11 by improving the existing model 11 using the feedback data 17. For example, the model generation unit 7 upgrades the model 11.

[0054] In this case, for example, model 11 can be generated as follows: A teacher dataset is prepared. In the teacher dataset, the input is input data 12 included in feedback data 17. In the teacher dataset, the correct output for this input is the download result 45 included in the feedback data 17. A new trained model is obtained by training this machine learning model in model 11. For example, new trained weighting coefficients in a neural network are obtained. The obtained trained model is called model 11.

[0055] (b) The model generation unit 7 generates a new model 11 when there is no existing model 11 and no feedback data 17.

[0056] In this case, for example, the model 11 can be generated as follows: A training dataset is prepared. This training dataset has the correct output (e.g., download results) when input data 12 is input. The correct output can be obtained, for example, by actually executing or simulating downloads in various situations that can be represented by the input data 12, using a test vehicle, etc. A machine learning model is trained using this training data to obtain a trained model. For example, trained weighting coefficients in a neural network are obtained. The obtained trained model is referred to as model 11.

[0057] In step 3, the model download unit 21 downloads the model 11 generated in step 2 from the cloud 3 to the vehicle 5.

[0058] The model 11 can be downloaded in the following manners (c) and (d), for example.

[0059] (c) Download both the machine learning model program (e.g., neural network program) and the parameters used in the machine learning model program (e.g., trained weighting coefficients in the neural network).

[0060] (d) For example, when updating or improving the parameters of the model 11 in the vehicle 5, download parameters (e.g., learned weighting coefficients in a neural network) used in the machine learning model program.

[0061] In step 4, the download permission determining unit 23 sets the model 11 downloaded in step 3. The download permission determining unit 23 uses the set model 11 when later determining whether or not a download is possible.

[0062] 3. Download Processing of Download Data 13 The download processing of the download data 13 will be described with reference to Fig. 3. This processing is executed by the vehicle 5. This processing is repeatedly executed at predetermined time intervals.

[0063] In step 11, the download permission determination unit 23 acquires the input data 12. Of the input data 12, the download data information 19 is acquired from the cloud 3. The other part of the input data 12 is stored in the vehicle 5.

[0064] In step 12, the download permission determination unit 23 determines whether or not the instruction receiving unit 35 has received a download instruction. If the download instruction has been received, the process proceeds to step 13. If the download instruction has not been received, the process proceeds to step 17.

[0065] In step 13, the download permission determining unit 23 determines whether the download data 13 can be downloaded and outputs a download permission determination result 14.

[0066] In step 14, the download processing unit 25 downloads the download data 13 from the cloud 3 to the vehicle 5. Note that in step 14, the download processing unit 25 downloads the download data 13 regardless of the content of the download permission determination result 14 in step 13. The download processing unit 25 also outputs a download result 45.

[0067] In step 15, the feedback unit 27 generates feedback data 17. The feedback data 17 includes the download result 45 obtained in step 14, the input data 12 used in step 13, the download possibility determination result 14 obtained in step 13, the ID of the model 11, and information indicating that a download instruction has been issued.

[0068] In step 16, the feedback unit 27 uploads the feedback data 17 generated in step 15 to the cloud 3. The uploaded feedback data 17 is acquired by the model generation unit 7 in step 1. The acquired feedback data 17 is used to generate the model 11 in step 2. In generating the model 11, feedback data 17 including information indicating that a download instruction has been issued is weighted more heavily than other feedback data 17.

[0069] For example, in generating the model 11, the learning rate in learning using feedback data 17 containing information indicating that a download instruction has been issued as training data may be set higher than the learning rate in learning using other feedback data 17 as training data.

[0070] For example, in generating the model 11, feedback data 17 in which the download result 45 and the download possibility determination result 14 do not match may be weighted more heavily than feedback data 17 in which the download result 45 and the download possibility determination result 14 match. For example, in generating the model 11, the learning rate in learning using feedback data 17 in which the download result 45 and the download possibility determination result 14 do not match may be set higher than the learning rate in learning using feedback data 17 in which the download result 45 and the download possibility determination result 14 match.

[0071] In step 17, the download permission determining unit 23 determines whether the instruction necessity information included in the download data information 19 indicates that a download instruction is necessary or that a download instruction is not necessary.

[0072] If the instruction necessity information indicates that a download instruction is not required, the process proceeds to step 18. If the instruction necessity information indicates that a download instruction is required, the process proceeds to step 24.

[0073] In step 18, the download permission determining unit 23 determines whether the download data 13 can be downloaded and outputs a download permission determination result 14.

[0074] In step 19, the download permission determination unit 23 determines whether the download permission determination result 14 obtained in step 18 indicates that downloading is permitted or not. If the download permission determination result 14 indicates that downloading is permitted, the process proceeds to step 20. If the download permission determination result 14 indicates that downloading is not permitted, the process proceeds to step 23.

[0075] In step 20, the download processing unit 25 downloads the download data 13 from the cloud 3 to the vehicle 5. The download processing unit 25 also outputs a download result 45.

[0076] In step 21, the feedback unit 27 generates feedback data 17. The feedback data 17 includes the download result 45 obtained in step 20, the input data 12 used in step 18, the download possibility determination result 14 obtained in step 18, and the ID of the model 11. Note that the feedback data 17 generated in step 21 differs from the feedback data 17 generated in step 15 in that it does not include information indicating that a download instruction has been issued.

[0077] In step 22, the feedback unit 27 uploads the feedback data 17 generated in step 21 to the cloud 3. The uploaded feedback data 17 is acquired by the model generation unit 7 in step 1. The acquired feedback data 17 is used to generate the model 11 in step 2.

[0078] In step 23, the download-disabled processing unit 33 executes a process for when downloading is disabled.

[0079] In step 24, the download permission determining unit 23 notifies the user of the vehicle 5. The notification includes information that the download data 13 was not downloaded.

[0080] 5. Effects of the System 1, Cloud 3, and Vehicle 5 (1A) If the download possibility determination unit 23 determines in step 18 that the download of the download data 13 is impossible, the download processing unit 25 does not download the download data 13 from the cloud 3 to the vehicle 5. If the download possibility determination unit 23 determines that the download of the download data 13 is impossible, this means that the download is likely to fail. Therefore, if the download is likely to fail, the download processing unit 25 does not download the download data 13 from the cloud 3 to the vehicle 5. As a result, the system 1 and the vehicle 5 can prevent the download of the download data 13 from failing.

[0081] (1B) The feedback unit 27 generates feedback data 17 and uploads it to the cloud 3. The model generation unit 7 generates a model 11 using the feedback data 17 uploaded by the feedback unit 27. As a result, the model generation unit 7 can generate a model 11 that can more accurately determine whether or not a download is possible. Note that being able to accurately determine whether or not a download is possible means that there is a high probability that the download possibility determination result 14 and the download result 45 will match.

[0082] (1C) The model 11 calculates the completion probability. The route suggestion unit 31 obtains the completion probability for each of a plurality of candidate driving routes using the model 11. The route suggestion unit 31 suggests the candidate driving route with the highest completion probability to the user of the vehicle 5 as the planned driving route for the vehicle 5. Therefore, the user of the vehicle 5 can select a planned driving route that is likely to result in successful download of the download data 13.

[0083] (1D) If the download possibility determination unit 23 determines that download of the download data 13 is not possible, the download impossibility processing unit 33 notifies the user of the vehicle 5 of spots located around the planned route of the vehicle 5 and the estimated time required to download the download data 13 at those spots.

[0084] The user of the vehicle 5 can move the vehicle 5 to the notified spot and download the download data 13. The user of the vehicle 5 can also know in advance the estimated time required to download the download data 13.

[0085] (1E) If the download possibility determination unit 23 determines that download of the download data 13 is not possible, the download impossibility processing unit 33 predicts the timing when download of the download data 13 will be possible in the future based on the driving history of the vehicle 5, the planned driving route of the vehicle 5, and the current state of the vehicle 5.

[0086] The download unavailability processing unit 33 notifies the user of the vehicle 5 of the predicted timing. Furthermore, the download availability determination unit 23 again determines whether the download data 13 can be downloaded at the predicted timing. If the result of this determination is that the download is available, the download processing unit 25 downloads the download data 13 from the cloud 3. Therefore, even if the download availability determination unit 23 determines that the download data 13 cannot be downloaded, there is a possibility that the download will be possible thereafter.

[0087] (1F) The instruction receiving unit 35 receives a download instruction from the driver of the vehicle 5. When the instruction receiving unit 35 receives the download instruction, the download processing unit 25 downloads the download data 13 from the cloud 3.

[0088] Furthermore, when the instruction receiving unit 35 receives a download instruction, the download permission determining unit 23 determines whether or not it is possible to download the download data 13. When the download processing unit 25 downloads the download data 13 from the cloud 3 in response to the download instruction, the feedback unit 27 generates feedback data 17 that further includes information indicating that a download instruction has been issued, and uploads the feedback data 17 to the cloud 3.

[0089] When creating the model 11, the cloud 3 assigns a higher weight to the feedback data 17 that further includes information indicating that a download instruction has been issued than to the other feedback data 17. This allows the model generation unit 7 to generate a model 11 that can more accurately determine whether or not a download is possible. <Other Embodiments> While the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments and can be implemented in various modifications.

[0090] (1) The input data 12 may not include one or more of the planned driving route data 41, the vehicle status data 43, and the download data information 19. The input data 12 may further include data other than the planned driving route data 41, the vehicle status data 43, and the download data information 19.

[0091] (2) The contents of the planned driving route data 41, the vehicle state data 43, and the download data information 19 may be different from those in the first embodiment.

[0092] (3) The vehicle 5 does not need to include the feedback unit 27. The model generation unit 7 does not need to use the feedback data 17 when generating the model 11.

[0093] (4) The feedback data 17 may not include one or more of the download result 45, the input data 12, the downloadability determination result 14, and the ID of the model 11. The feedback data 17 may also include other information.

[0094] (5) The vehicle 5 does not need to perform processing when downloading is not possible.

[0095] (6) In the first embodiment, the system 1 includes the cloud 3 as an off-vehicle system. The system 1 may include an on-premise system outside the vehicle 5 instead of the cloud 3. In this case, the on-premise system outside the vehicle 5 has the same functions as the cloud 3 in the first embodiment. The system 1 may also include a combination of the cloud 3 and the on-premise system outside the vehicle 5. In this case, the combination of the cloud 3 and the on-premise system outside the vehicle 5 has the same functions as the cloud 3 in the first embodiment.

[0096] (7) The model generation unit 7, model download unit 21, download possibility determination unit 23, download processing unit 25, feedback unit 27, route suggestion unit 31, download impossible processing unit 33, and the methods thereof described in the present disclosure may be realized by a dedicated computer provided by configuring a processor and memory programmed to execute one or more functions embodied in a computer program.

[0097] Alternatively, the model generation unit 7, model download unit 21, download possibility determination unit 23, download processing unit 25, feedback unit 27, route proposal unit 31, download unsuccessful processing unit 33, and the methods thereof described in the present disclosure may be realized by a dedicated computer provided by configuring a processor with one or more dedicated hardware logic circuits.

[0098] Alternatively, the model generation unit 7, model download unit 21, download possibility determination unit 23, download processing unit 25, feedback unit 27, route proposal unit 31, download unavailability processing unit 33, and the methods thereof described in the present disclosure may be realized by one or more dedicated computers configured by combining a processor and memory programmed to perform one or more functions with a processor configured by one or more hardware logic circuits. Also, the computer program may be stored in a computer-readable non-transitory tangible recording medium as instructions to be executed by the computer.

[0099] The method for realizing the functions of each part included in the model generation part 7, model download part 21, download possibility determination part 23, download processing part 25, feedback part 27, route suggestion part 31, and download impossible processing part 33 does not necessarily have to include software, and all of the functions may be realized using one or more pieces of hardware.

[0100] (8) Multiple functions of one component in the above embodiments may be realized by multiple components, or one function of one component may be realized by multiple components. Also, multiple functions of multiple components may be realized by one component, or one function realized by multiple components may be realized by one component. Also, part of the configuration of the above embodiments may be omitted. Also, at least part of the configuration of the above embodiments may be added to or substituted for the configuration of another of the above embodiments.

[0101] (9) In addition to the above-described system 1, the present disclosure can also be realized in various forms, such as a higher-level system that includes the system 1 as a component, a program for causing a computer to function as the model generation unit 7, the model download unit 21, the download possibility determination unit 23, the download processing unit 25, the feedback unit 27, the route suggestion unit 31, and the download unsuccessful processing unit 33, a non-transient physical recording medium such as a semiconductor memory on which this program is recorded, a method for manufacturing the system 1, a method for manufacturing the vehicle 5, etc. [Technical Ideas Disclosed in the Present Specification] [Item 1] A system (1) comprising an off-vehicle system (3) and a vehicle (5), wherein the off-vehicle system comprises: a model generation unit (7) configured to generate a model (11) that determines whether download data (13) can be downloaded from the off-vehicle system to the vehicle; and an off-vehicle system side storage unit (9) configured to store the download data; and the vehicle comprises: a model download unit (21) configured to download the model from the off-vehicle system to the vehicle; a download possibility determination unit (23) configured to determine whether the download data can be downloaded in accordance with a determination result (14) when input data (12) that represents a condition that affects the download of the download data is input to the model downloaded by the model download unit; and a download processing unit (25) configured to download the download data from the off-vehicle system to the vehicle when the download possibility determination unit determines that the download data can be downloaded. [Item 2] The system according to item 1, wherein the vehicle further comprises a feedback unit (27) configured to generate feedback data (17) including a result of the download (45) by the download processing unit, the input data, the determination result, and an ID of the model, and upload the feedback data to the off-vehicle system, and the model generation unit is configured to generate the model using the feedback data uploaded by the feedback unit.[Item 3] The system according to item 1 or 2, wherein the model is configured to calculate a probability of completing the download of the download data, and the vehicle further comprises a route proposing unit (31) configured to use the model to obtain the probability for each of a plurality of candidate driving routes and to propose the candidate driving route with the highest probability to a user of the vehicle as a planned driving route for the vehicle. [Item 4] The system according to any one of items 1 to 3, wherein the vehicle further comprises a spot notifying unit (33) configured, when the download feasibility determination unit determines that the download data cannot be downloaded, to the user of the vehicle of spots located in the vicinity of the planned driving route of the vehicle and an estimated time required to download the download data at each spot. [Item 5] A system according to any one of items 1 to 4, wherein the vehicle further comprises: a timing prediction unit (33) configured to predict a timing when the download data will be available for download in the future based on the driving history of the vehicle, the planned driving route of the vehicle, and the current state of the vehicle when the download possibility determination unit determines that the download data cannot be downloaded; and a timing notification unit (33) configured to notify a user of the vehicle of the timing, wherein the download possibility determination unit is configured to re-determine whether the download data can be downloaded at the timing.[Item 6] The system according to Item 2, wherein the vehicle further comprises an instruction receiving unit (35) configured to receive a download instruction from a driver of the vehicle, the download processing unit is configured to download the download data from the extra-vehicle system when the instruction receiving unit receives the download instruction, the download possibility determination unit is configured to determine whether the download data can be downloaded when the instruction receiving unit receives the download instruction, and the feedback unit is configured to generate the feedback data further including information indicating that the download instruction has been issued, and upload the feedback data to the extra-vehicle system when the download processing unit downloads the download data from the extra-vehicle system in response to the download instruction. [Item 7] An extra-vehicle system (3), comprising: a model generation unit (7) configured to generate a model (11) that determines whether download data (13) can be downloaded from the extra-vehicle system to the vehicle (5), and provide the model to the vehicle, and an extra-vehicle system-side storage unit (9) configured to store the download data and provide it to the vehicle. [Item 8] A vehicle (5) comprising: a model download unit (21) configured to download, from an extra-vehicle system (3), a model (11) that determines whether download data (13) can be downloaded from the extra-vehicle system to the vehicle; a download possibility determination unit (23) configured to determine whether downloading of the download data is possible in accordance with a determination result (14) when input data (12) that represents conditions that affect the download of the download data is input to the model downloaded by the model download unit; and a download processing unit (25) configured to download the download data from the extra-vehicle system to the vehicle when the download possibility determination unit determines that downloading of the download data is possible.

Claims

1. A system (1) comprising an external vehicle system (3) and a vehicle (5), The aforementioned external vehicle system is A model generation unit (7) is configured to generate a model (11) that determines whether or not the download data (13) from the external vehicle system to the vehicle can be downloaded, A system-side storage unit (9) outside the vehicle is configured to store the downloaded data, Equipped with, The aforementioned vehicle is A model download unit (21) configured to download the model from the external vehicle system to the vehicle, A download feasibility determination unit (23) is configured to determine whether or not to download the download data according to the determination result (14) when input data (12) representing conditions affecting the download of the download data is input to the model downloaded by the model download unit, If the download feasibility determination unit determines that the download data can be downloaded, a download processing unit (25) configured to download the download data from the external vehicle system to the vehicle, Equipped with, The vehicle further comprises a feedback unit (27) configured to generate feedback data (17) including the download result (45) by the download processing unit, the input data, the determination result, and the model ID, and upload it to the external vehicle system. The model generation unit is configured to generate the model using the feedback data uploaded by the feedback unit. The vehicle further includes an instruction receiving unit (35) configured to receive download instructions from the driver of the vehicle, The download processing unit is configured to download the download data from the external vehicle system when the instruction receiving unit receives the instruction to download. The download eligibility determination unit is configured to determine whether or not the download data can be downloaded when the instruction receiving unit receives the instruction to download. The feedback unit is configured to generate feedback data, which further includes information indicating that a download instruction was given, when the download processing unit downloads the download data from the external vehicle system in response to the download instruction, and upload it to the external vehicle system. In the generation of the model by the model generation unit, the feedback data, which further includes information indicating that the download instruction was given, is given a greater weight than the other feedback data. system.

2. A system (1) comprising an external system (3) and a vehicle (5), The aforementioned external vehicle system is A model generation unit (7) is configured to generate a model (11) that determines whether or not the download data (13) from the external vehicle system to the vehicle can be downloaded, A system-side storage unit (9) outside the vehicle is configured to store the downloaded data, Equipped with, The aforementioned vehicle is A model download unit (21) configured to download the model from the external vehicle system to the vehicle, A download feasibility determination unit (23) is configured to determine whether or not to download the download data according to the determination result (14) when input data (12) representing conditions affecting the download of the download data is input to the model downloaded by the model download unit, If the download feasibility determination unit determines that the download data can be downloaded, a download processing unit (25) configured to download the download data from the external vehicle system to the vehicle, Equipped with, The vehicle further comprises a feedback unit (27) configured to generate feedback data (17) including the download result (45) by the download processing unit, the input data, the determination result, and the model ID, and upload it to the external vehicle system. The model generation unit is configured to generate the model using the feedback data uploaded by the feedback unit. The vehicle further includes an instruction receiving unit (35) configured to receive download instructions from the driver of the vehicle, The download eligibility determination unit is configured to determine whether or not the download data can be downloaded when the instruction receiving unit receives the instruction to download. The download processing unit is configured to download the download data from the external vehicle system regardless of the determination result when the instruction receiving unit receives the instruction to download. system.

3. The system according to claim 1 or 2, The aforementioned model is configured to calculate the probability of successfully completing the download of the aforementioned data. The vehicle further includes a route proposal unit (31) configured to obtain the accuracy for each of a plurality of candidate routes using the model, and propose the candidate route with the highest accuracy to the vehicle's user as the vehicle's planned route. system.

4. The system according to claim 1 or 2, If the download feasibility determination unit determines that the download of the download data is impossible, the vehicle is equipped with a spot notification unit (33) configured to notify the vehicle's user of spots located around the vehicle's planned route and the estimated time required to download the download data at those spots. To prepare further, system.

5. The system according to claim 1 or 2, The aforementioned vehicle is If the download feasibility determination unit determines that the download of the aforementioned download data is impossible, the timing prediction unit (33) is configured to predict the timing at which the download of the aforementioned download data will become possible in the future, based on the vehicle's driving history, the vehicle's planned driving route, and the current state of the vehicle. A timing notification unit (33) configured to notify the user of the vehicle of the aforementioned timing, Furthermore, The download eligibility determination unit is configured to determine again whether the download data can be downloaded at the aforementioned timing. system.

6. The system according to claim 1 or 2, The input data includes information on the amount or speed of data to be downloaded along the vehicle's planned route, the vehicle's make or model, the vehicle's network strength, the specifications of the ECU installed in the vehicle, or the operating history or resource usage history of the ECU installed in the vehicle. system.

7. External vehicle system (3), A model generation unit (7) is configured to generate a model (11) that determines whether or not the download data (13) from the external vehicle system to the vehicle (5) can be downloaded, and to provide it to the vehicle. A vehicle-external system-side storage unit (9) is configured to store the downloaded data and provide it to the vehicle, An external vehicle system equipped with the following features.

8. The external vehicle system according to claim 7, The vehicle is configured to determine whether or not to download the download data according to the determination result (14) when input data (12) representing conditions affecting the download of the download data is input to the model. The input data includes information on the amount or speed of data to be downloaded along the vehicle's planned route, the vehicle's make or model, the vehicle's network strength, the specifications of the ECU installed in the vehicle, or the operating history or resource usage history of the ECU installed in the vehicle. External vehicle systems.

9. Vehicle (5), A model download unit (21) is configured to download a model (11) from the external vehicle system (3) to the vehicle, which determines whether or not to download download data (13). A download feasibility determination unit (23) is configured to determine whether or not to download the download data according to the determination result (14) when input data (12) representing conditions affecting the download of the download data is input to the model downloaded by the model download unit, If the download feasibility determination unit determines that the download data can be downloaded, a download processing unit (25) configured to download the download data from the external vehicle system to the vehicle, Equipped with, vehicle.

10. The vehicle according to claim 9, The input data includes information on the amount or speed of data to be downloaded along the vehicle's planned route, the vehicle's make or model, the vehicle's network strength, the specifications of the ECU installed in the vehicle, or the operating history or resource usage history of the ECU installed in the vehicle. vehicle.