Information processing system, information processing device, and information processing method

Abstract

An information processing system according to an embodiment of the present disclosure comprises: a plurality of reference vehicles that belong to a prescribed vehicle group; a target vehicle that is a vehicle different from the plurality of reference vehicles; and an information processing device that is configured to predict a temporal deterioration tendency pertaining to components included in this target vehicle. This information processing device comprises: a first acquisition unit configured to collect, for each component included in each of the plurality of reference vehicles, component deterioration data indicating a correspondence relationship between the degree of deterioration of the component and a time-dependent element, and to acquire, as reference deterioration data, an aggregate of pieces of component deterioration data pertaining to the plurality of reference vehicles; a second acquisition unit configured to acquire, as target deterioration data, component deterioration data pertaining to the target vehicle; and a prediction unit configured to predict a deterioration tendency pertaining to the components included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit.

Description

Information processing system, information processing device, and information processing method

[0001] The present disclosure relates to an information processing device and information processing method that perform predetermined predictions regarding parts included in a target vehicle, and an information processing system that includes such an information processing device.

[0002] Various methods have been proposed as systems for providing maintenance information related to parts included in a vehicle (see, for example, Patent Document 1).

[0003] WO2015 / 132947 publication

[0004] An information processing system according to an embodiment of the present disclosure includes a plurality of reference vehicles belonging to a predetermined vehicle group, a target vehicle that is a vehicle different from the plurality of reference vehicles, and an information processing device configured to predict a deterioration trend over time for parts included in the target vehicle. The information processing device includes a first acquisition unit configured to collect part deterioration data indicating a correspondence between the degree of deterioration of the part and a temporal factor for each part included in the plurality of reference vehicles, and to acquire a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data, a second acquisition unit configured to acquire the part deterioration data for the target vehicle as target deterioration data, and a prediction unit configured to predict a deterioration trend for the part included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit.

[0005] An information processing device according to one embodiment of the present disclosure is a device configured to predict the deterioration trend over time of parts included in a target vehicle, which is a vehicle different from a plurality of reference vehicles belonging to a predetermined vehicle group, and includes: a first acquisition unit configured to collect part deterioration data indicating the correspondence between the degree of deterioration of the part and temporal factors for each part included in the plurality of reference vehicles, and to acquire a collection of part deterioration data for the plurality of reference vehicles as reference deterioration data; a second acquisition unit configured to acquire part deterioration data for the target vehicle as target deterioration data; and a prediction unit configured to predict the deterioration trend of parts included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit.

[0006] An information processing method according to one embodiment of the present disclosure is a method for predicting the deterioration trend over time of parts included in a target vehicle, which is a vehicle different from a plurality of reference vehicles belonging to a predetermined vehicle group, and includes collecting part deterioration data indicating the correspondence between the degree of deterioration of the part and time-varying factors for each part included in each of the plurality of reference vehicles, obtaining a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data, obtaining part deterioration data for the target vehicle as target deterioration data, and predicting the deterioration trend of the parts included in the target vehicle by comparing the reference deterioration data with the target deterioration data.

[0007] The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate one embodiment and, together with the description, serve to explain the principles of the disclosure.

[0008] FIG. 1 is a schematic diagram illustrating an example of a general configuration of an information processing system according to an embodiment of the present disclosure. FIG. 2 is a block diagram illustrating an example of a detailed configuration of the information processing system illustrated in FIG. 1. FIG. 3 is a characteristic diagram illustrating an example of various parts deterioration data for a plurality of reference vehicles and a target vehicle. FIG. 4 is a flowchart illustrating an example of a process for predicting a deterioration trend of a part according to an embodiment. FIG. 5 is a schematic diagram illustrating an example of notification content for a user of a target vehicle. FIG. 6 is a block diagram illustrating an example of a detailed configuration of an information processing system according to a modified example of the present disclosure. FIG. 7A is a flowchart illustrating an example of a process for predicting a deterioration trend of a part according to a modified example. FIG. 7B is a flowchart illustrating an example of a process for predicting a deterioration trend of a part following FIG. 7A.

[0009] Maintenance information about parts included in a vehicle may include a predicted result of the deterioration trend of the part. When predicting the deterioration trend of parts included in such a vehicle (a vehicle to be predicted), it is necessary to improve the prediction accuracy.

[0010] It is desirable to provide an information processing system, an information processing device, and an information processing method that can improve the accuracy of predicting the deterioration tendency of parts included in a target vehicle.

[0011] Some exemplary embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that the following description illustrates one specific example of the present disclosure and should not be construed as limiting the present disclosure. For example, each element, including numerical values, shapes, materials, parts, the position of each part, and the connection method of each part, is merely an example and should not be construed as limiting the present disclosure. Furthermore, in the following exemplary embodiments, components not described in independent claims based on the highest concept of the present disclosure are optional and may be provided as needed. The drawings are schematic and are not intended to be drawn to scale. Throughout this specification and the drawings, components having substantially the same function and configuration are designated by the same reference numerals, and redundant description will be omitted. Furthermore, components not directly related to one embodiment of the present disclosure are not shown in the drawings.

[0012] <Embodiment> [Configuration Example] Fig. 1 is a schematic diagram illustrating an example of the overall configuration of an information processing system (information processing system 4) according to an embodiment of the present disclosure. Fig. 2 is a block diagram illustrating an example of the detailed configuration of the information processing system 4 illustrated in Fig. 1.

[0013] This information processing system 4 is a system for predicting the deterioration tendency over time of parts included in a target vehicle 2 (a system for predicting the deterioration tendency of vehicle parts). As shown in Figures 1 and 2 , the information processing system 4 includes a plurality of reference vehicles 1 belonging to a predetermined vehicle group (vehicle group) 10, a target vehicle 2 that is a vehicle for which the deterioration tendency is to be predicted, and an information processing device 3 that predicts the deterioration tendency of parts included in this target vehicle 2.

[0014] Note that an information processing method (a method for predicting the deterioration trend of a vehicle part) according to an embodiment of the present disclosure is embodied by the operation of this information processing system 4, and will therefore be described together below. Furthermore, the parts (vehicle parts) whose deterioration trends are predicted as described above include various consumable parts and replacement parts, such as batteries, brake pads, engine oil, tires, and wipers. In this embodiment (and a modified example described later), an example will be described in which the part whose deterioration trend is predicted as described above is a battery.

[0015] (Target vehicle 2) The target vehicle 2 is a vehicle owned by a user (owner) 9, and is a vehicle different from the above-mentioned plurality of reference vehicles 1. As shown in Figures 1 and 2, this target vehicle 2 is equipped with a vehicle control unit 21, a battery 22, and a communicator 23. It is assumed that the user 9 of this target vehicle 2 has an information device 9 having a display unit 90a.

[0016] The vehicle control unit 21 is a component (control unit) that controls various operations in the target vehicle 2 and performs various arithmetic processing. Specifically, the vehicle control unit 21 includes, for example, one or more processors (CPU: Central Processing Unit) that execute programs and one or more memories communicatively connected to these processors. Furthermore, such memories include, for example, RAM (Random Access Memory) that temporarily stores processing data and ROM (Read Only Memory) that stores programs.

[0017] In the example shown in FIG. 2 , the vehicle control unit 21 includes a driving control unit 211 , a battery control unit 212 , a communication control unit 213 , and an information acquisition unit 214 .

[0018] The driving control unit 211 is a unit that controls the driving operation of the target vehicle 2, and performs overall control regarding the driving of the target vehicle 2. Specifically, the driving control unit 211 controls, for example, the drive system, braking system, steering system, etc. of the target vehicle 2.

[0019] The battery control unit 212 is a unit that controls the operation (charging operation, discharging operation, etc.) of the battery 22, which will be described later. The communication control unit 213 is a unit that controls the communication operation of the communicator 23, which will be described later.

[0020] The information acquisition unit 214 is a unit that acquires various information (vehicle data Dv2) related to the target vehicle 2. Examples of such vehicle data Dv2 include the vehicle identification number of the target vehicle 2, driving information (such as mileage and image data of the surroundings of the target vehicle 2), and information indicating the usage status of parts (such as the internal resistance value of the battery 22).

[0021] The battery 22 is a component that functions as a power source for the target vehicle 2, and is configured using various types of secondary batteries such as lithium ion batteries. As described above, the battery 22 corresponds to a specific example of a "component" according to an embodiment of the present disclosure.

[0022] The communicator 23 is a device that communicates with the information processing device 3. The communicator 23 transmits the vehicle data Dv2 acquired by the information acquisition unit 214 to the information processing device 3, as shown in, for example, FIGS.

[0023] (Information Processing Device 3) The information processing device 3 is configured using, for example, a server, and includes an information processing unit 31 as shown in Figures 1 and 2. Note that the information processing device 3 is installed in a vehicle manufacturer 30, for example, as shown in Figure 1.

[0024] The information processing unit 31 is a unit (arithmetic processing unit) that performs various types of arithmetic processing. Specifically, the information processing unit 31 includes, for example, one or more processors (CPUs) that execute programs and one or more memories that are communicatively connected to these processors. Such memories include, for example, RAM that temporarily stores processing data and ROM that stores programs.

[0025] 2, the information processing unit 31 includes data acquisition units 311 and 312, a prediction unit 313, an estimation unit 314, and an information providing unit 315. Note that the data acquisition unit 311 corresponds to a specific example of a "first acquisition unit" according to an embodiment of the present disclosure, and the data acquisition unit 312 corresponds to a specific example of a "second acquisition unit" according to an embodiment of the present disclosure.

[0026] As shown in FIGS. 1 and 2 , the data acquisition unit 311 is a unit that acquires part degradation data (reference degradation data Dd10) for the vehicle group 10 (plurality of reference vehicles 1) based on the vehicle data Dv10 (a collection of multiple vehicle data Dv1) collected from the vehicle group 10 (plurality of reference vehicles 1). Specifically, the data acquisition unit 311 collects part degradation data Dd1 for each part (battery in this example) included in each reference vehicle 1 based on the vehicle data Dv1 for each of the multiple reference vehicles 1. The data acquisition unit 311 then acquires the collection of part degradation data Dd1 for the multiple reference vehicles 1 as the reference degradation data Dd10. Note that, like the vehicle data Dv2 described above, the vehicle data Dv1 can also include, for example, the vehicle identification number of each reference vehicle 1, driving information (such as mileage and image data of the surroundings of each reference vehicle 1), and information indicating the usage status of parts (such as the internal resistance value of the battery included in each reference vehicle 1).

[0027] As shown in Figures 1 and 2, the data acquisition unit 312 is a unit that acquires part deterioration data regarding the target vehicle 2 as target deterioration data Dd2 based on vehicle data Dv2 transmitted from the target vehicle 2 (communication device 23).

[0028] The above-mentioned various types of part deterioration data (part deterioration data Dd1, reference deterioration data Dd10, and target deterioration data Dd2) will now be described in detail with reference to Figure 3. Figure 3 shows an example of various types of part deterioration data for multiple reference vehicles 1 and target vehicles 2 as a characteristic diagram. Note that in Figure 3, the remaining battery charge status in each state is schematically indicated by the symbols G0, G11 to G13, G21, G22, and G23.

[0029] 3 shows a collection of multiple pieces of part deterioration data Dd1 for each of multiple reference vehicles 1 (reference deterioration data Dd10 for a vehicle group 10 to which the multiple reference vehicles 1 belong) and part deterioration data (target deterioration data Dd2) for a target vehicle 2. Each piece of part deterioration data Dd1 and each piece of target deterioration data Dd2 indicate the correspondence between the degree of deterioration of a part (e.g., the internal resistance value of a battery) and a time-dependent factor (e.g., the duration of use).

[0030] In the reference deterioration data Dd10, which is an aggregate of multiple pieces of part deterioration data Dd1, the deterioration trends over time of the parts in the vehicle fleet 10 are shown using a deterioration trend line C10. Furthermore, the deterioration trends over time of the parts in the target vehicle 2 based on the target deterioration data Dd2 are shown using deterioration prediction lines C21 to C23. Specifically, a first example of the deterioration trend based on the target deterioration data Dd2 (one example of the deterioration trend of the parts in the target vehicle 2) is shown using the deterioration prediction lines C21 and C22. Furthermore, a second example of the deterioration trend based on the target deterioration data Dd2 (another example of the deterioration trend of the parts in the target vehicle 2) is shown using the deterioration prediction line C23. Both of the deterioration trends in these first and second examples are stronger (larger) than the deterioration trend in the vehicle fleet 10. Furthermore, compared to the deterioration trend in the first example (deterioration trend using deterioration prediction lines C21 and C22), the deterioration trend in the second example (deterioration trend using deterioration prediction line C23) is even stronger.

[0031] The prediction unit 313 is a unit that predicts the deterioration tendency of the parts included in the target vehicle 2 by comparing the reference deterioration data Dd10 acquired by the data acquisition unit 311 with the target deterioration data Dd2 acquired by the data acquisition unit 312. Details of the prediction process in the prediction unit 313 will be described later (FIGS. 4 and 5).

[0032] The estimation unit 314 is a unit that estimates one or more deterioration factors and the contribution rate of each of the deterioration factors for the parts included in the target vehicle 2 based on the target deterioration data Dd2 described above.

[0033] The information providing unit 315 is a unit that provides to the outside vehicle maintenance information Im of the target vehicle 2, including the prediction results by the prediction unit 313 (prediction results of deterioration trends related to parts) and the estimation results by the estimation unit 314 (the above-mentioned deterioration factors and contribution rates). Specifically, in the example shown in Fig. 2, the information providing unit 315 provides the vehicle maintenance information Im, including such prediction results and estimation results, to a user 9 (information device 90) of the target vehicle 2 and an employee 8 (a PC (Personal Computer) 38 used by the employee 8) within the vehicle manufacturer 30.

[0034] Furthermore, if the deterioration trend of the part in the target vehicle 2 predicted by the prediction unit 313 is stronger than the deterioration trend of the part in the vehicle fleet 10 indicated by the reference deterioration data Dd10, the information provision unit 315 issues a predetermined notification when providing the above-mentioned vehicle maintenance information Im. That is, in such a case, the information provision unit 315 issues a predetermined notification to each of the user 9 (information device 90) of the target vehicle 2 and the employee 8 (PC 38) of the vehicle manufacturer 30. Furthermore, as will be described in detail later ( FIG. 5 ), the information provision unit 315 changes the content of the notification at that time depending on the degree of the deterioration trend of the part in the target vehicle 2 and the deterioration factor and contribution rate estimated by the estimation unit 314.

[0035] The information providing unit 315 corresponds to a specific example of an "information providing unit" and a "notification unit" according to an embodiment of the present disclosure.

[0036] [Operation, Function, and Effect] Next, the operation, function, and effect of this embodiment will be described in detail.

[0037] (A. General Vehicle Maintenance) First, during general vehicle maintenance, for example, predetermined parameters (such as the period of use of the parts and the mileage of the vehicle) are set for the various parts inside the vehicle described above, so that maintenance reminders for periodic inspections, etc. are issued. In other words, by using such predetermined parameters, the deterioration tendency of the parts is uniformly predicted regardless of the condition of each vehicle.

[0038] However, in reality, the degree of deterioration of vehicle parts varies depending on the vehicle usage conditions of each user, so the vehicle maintenance period needs to be set for each user. As such, general vehicle maintenance does not reflect the specific conditions of the vehicle parts (the degree of deterioration of the parts), and it can be said that the accuracy of predicting the deterioration tendency of parts may be insufficient.

[0039] (B. Example of process for predicting deterioration trends of parts) Therefore, the information processing system 4 of this embodiment is configured to predict the deterioration trends over time of parts (in this example, the battery 22) included in the target vehicle 2, for example, as follows.

[0040] Fig. 4 is a flowchart showing an example of a process for predicting a deterioration tendency of a part (prediction process in the information processing device 3) according to this embodiment. Fig. 5 is a schematic diagram showing an example of the content of a notification sent to the user 9 (information device 90) of the target vehicle 2.

[0041] 4 , first, the data acquisition unit 311 acquires vehicle data Dv10 for the vehicle fleet 10 (vehicle data Dv1 for each of the plurality of reference vehicles 1) from the plurality of reference vehicles 1 belonging to the vehicle fleet 10 (step S11). Next, the data acquisition unit 311 performs a predetermined extraction process based on the acquired vehicle data Dv for each reference vehicle 1 to acquire part deterioration data Dd1 for each of the plurality of reference vehicles 1 (step S12). Then, the data acquisition unit 311 acquires a collection of the plurality of part deterioration data Dd1 as reference deterioration data Dd10 (step S13).

[0042] Next, the data acquisition unit 312 acquires vehicle data Dv2 regarding the target vehicle 2 from the target vehicle 2 (communicator 23) and performs a predetermined extraction process based on the acquired vehicle data Dv2 to acquire part deterioration data (target deterioration data Dd2) regarding the target vehicle 2 (step S14).

[0043] Next, the prediction unit 313 compares the reference deterioration data Dd10 and the target deterioration data Dd2 thus acquired to predict the deterioration trends of the parts included in the target vehicle 2 (step S15). Specifically, the prediction unit 313 predicts the deterioration trends of the parts included in the target vehicle 2 based on a predetermined analysis process using the comparison between the reference deterioration data Dd10 and the target deterioration data Dd2.

[0044] Next, the prediction unit 313 determines whether the predicted deterioration trend of the part in the target vehicle 2 (the deterioration trend in the target deterioration data Dd2) is stronger (greater) than the deterioration trend of the part in the vehicle fleet 10 (the deterioration trend in the reference deterioration data Dd10) (step S16). If it is determined that the deterioration trend in the target deterioration data Dd2 is weaker (smaller) than the deterioration trend in the reference deterioration data Dd10 (step S16: N), the process proceeds to step S19, which will be described later.

[0045] On the other hand, if it is determined that the deterioration trend in the target deterioration data Dd2 is stronger than the deterioration trend in the reference deterioration data Dd10 (step S16: Y), the following occurs. That is, in this case, the prediction unit 313 determines the magnitude of the deterioration trend of the parts in the target vehicle 2, and the estimation unit 314 estimates one or more deterioration factors and the contribution rate of each deterioration factor for the parts included in the target vehicle 2 based on the target deterioration data Dd2 (step S17). Next, the information provision unit 315 provides a predetermined notification to the user 9 (information device 90) of the target vehicle 2, etc., as described above (step S18). At this time, the information provision unit 315 sets the notification content according to the magnitude of the deterioration trend of the parts in the target vehicle 2, the deterioration factors, and the contribution rates determined or estimated in step S17.

[0046] Specifically, as shown in FIG. 5, for example, notifications are made in levels (levels from "Level 1" to "Level 3" indicated by the dashed arrows in FIG. 5) according to the magnitude of the deterioration trend, the deterioration factors, and the contribution rate.

[0047] 5, first, in the notification content of "Level 1 (standard)", notification M1 corresponding to an abnormal notification of a deterioration tendency is displayed on the information device 90 (display unit 90a) of the user 9. In detail, in this example of notification M1, a comment saying "The battery is deteriorating. We recommend that you have it inspected at your local dealer" is displayed together with a schematic diagram of the battery.

[0048] Furthermore, in the notification content of "Level 2," notification M2 corresponding to improvement advice based on the cause of deterioration is displayed on the information device 90 (display unit 90a) of the user 9. In this example of notification M2, in detail, a comment stating "Battery deterioration is accelerating due to XX. You can slow down the deterioration by doing △△" is displayed together with a schematic diagram corresponding to the part deterioration data Dd2 described above.

[0049] Furthermore, in the notification content of "Level 3," notification M3 corresponding to the deterioration time and improvement effect is displayed on the information device 90 (display unit 90a) of the user 9. In detail, this example of notification M3 displays the comment "If used as is, the battery may need to be replaced in XX months. By performing □□□, the deterioration can be delayed by up to XX months," along with a schematic diagram corresponding to the part deterioration data Dd2 described above.

[0050] Next, the information provider 315 provides the vehicle maintenance information Im of the target vehicle 2, including the prediction results of step S15 (prediction results of deterioration trends for parts of the target vehicle 2), to the user 9 (information device 90) of the target vehicle 2 (step S19). At this time, as described above, the estimation results of step S17 (the estimation results of the aforementioned deterioration factors and contribution rates) may also be included in the vehicle maintenance information Im.

[0051] This completes the series of processes shown in FIG.

[0052] (C. Functions and Effects) In this manner, in this embodiment, a collection of part deterioration data Dd1 for multiple reference vehicles 1 belonging to a specified vehicle group 10 (reference deterioration data Dd10) is compared with part deterioration data for a target vehicle 2 (target deterioration data Dd2), thereby predicting the deterioration trend for parts included in the target vehicle 2.

[0053] As a result, in this embodiment, unlike the case where the deterioration tendency of a part is uniformly predicted using predetermined parameters (such as the period of use of the part or the mileage of the vehicle), as described above, the following occurs: That is, a prediction of the deterioration tendency of a part is realized that reflects the specific conditions of the parts in the target vehicle 2 (the degree of deterioration compared to a plurality of reference vehicles 1). As a result, in this embodiment, it is possible to improve the accuracy of prediction of the deterioration tendency of parts included in the target vehicle 2.

[0054] Furthermore, in this embodiment, vehicle maintenance information Im including predicted results of deterioration trends for parts included in the target vehicle 2 is provided to the user 9 (information device 90) of the target vehicle 2, resulting in the following: That is, such predicted results of deterioration trends can be used to perform maintenance on the target vehicle 2, thereby improving convenience. Furthermore, in this embodiment, such vehicle maintenance information Im is also provided to an employee 8 (PC 38) within the vehicle manufacturer 30, making it possible to utilize such predicted results of deterioration trends within the vehicle manufacturer 30.

[0055] Furthermore, in this embodiment, if the predicted deterioration trend of a part in the target vehicle 2 is stronger than the deterioration trend of a part in the vehicle fleet 10, as indicated by the reference deterioration data Dd10, a predetermined notification is sent to the user 9 (information device 90) of the target vehicle 2, as follows: In other words, the user 9 of the target vehicle 2 can know in advance that the prediction result shows a strong deterioration trend, thereby improving convenience.

[0056] Additionally, in this embodiment, the content of the notification to the user 9 of the target vehicle 2 is changed depending on the deterioration trend of parts in the target vehicle 2 and the magnitude of the estimated deterioration factors and contribution rates, as follows: That is, the user 9 can receive notification content that reflects such detailed information about the deterioration of parts of the target vehicle 2 in advance, thereby further improving convenience. Furthermore, by changing the notification content (classifying it into levels) in this way, it is possible to provide useful notification advice to the user 9 of the target vehicle 2 and to use the notification content to respond to inquiries from the user 9.

[0057] <Modifications> Next, modifications of the above embodiment will be described. Note that, in the following, the same components as those in the embodiment will be given the same reference numerals, and descriptions thereof will be omitted as appropriate.

[0058] [Configuration Example] Figure 6 is a block diagram showing a detailed configuration example of an information processing system (information processing system 4A) according to a modified example. The information processing system 4A of this modified example corresponds to the information processing system 4 of the embodiment shown in Figure 2, except that an information processing device 3A, which will be described below, is provided instead of the information processing device 3, and the other configurations are similar. Note that the information processing method according to the modified example of the present disclosure (a method for predicting the deterioration tendency of a vehicle part) is embodied by the operation of this information processing system 4A, and will therefore also be described below.

[0059] (Information processing device 3A) The information processing device 3A corresponds to the information processing device 3 of the embodiment shown in Figure 2, except that an information processing unit 31A described below is provided instead of the information processing unit 31, and the other configurations are similar.

[0060] This information processing unit 31A corresponds to the information processing unit 31 of the embodiment shown in Figure 2, to which a control change unit 316 described below has been further provided (added), and the other configurations are similar.

[0061] The information processing unit 31A is a unit (arithmetic processing unit) that performs various types of arithmetic processing, similar to the information processing unit 31. Specifically, the information processing unit 31A includes, for example, one or more processors (CPUs) that execute programs and one or more memories communicably connected to these processors. The memory includes, for example, a RAM that temporarily stores processing data and a ROM that stores programs.

[0062] When the deterioration tendency of the parts in the target vehicle 2 predicted by the prediction unit 313 is stronger than the deterioration tendency of the parts in the vehicle fleet 10 indicated by the reference deterioration data Dd10, the control change unit 316 changes the content of the vehicle control executed in the target vehicle 2 (vehicle control unit 21). Specifically, the control change unit 316 changes the content of the vehicle control executed in the target vehicle 2 so as to reduce the deterioration tendency of the parts in the target vehicle 2 (slow the deterioration of the parts). Note that such a change in the content of the vehicle control is performed using control content change data Dc transmitted from the control change unit 316 to the target vehicle 2 (communicator 23), as shown in FIG. 6 .

[0063] [Operations, Functions, and Effects] (Example of Prediction Processing According to Modification) Figures 7A and 7B are flowcharts showing an example of a process for predicting a deterioration tendency of a part according to a modification (prediction processing in information processing device 3A). The example of processing shown in Figures 7A and 7B is obtained by adding step S20, which will be described below, between steps S18 and S19 (immediately after step S18) in the example of processing shown in Figure 4 described in the embodiment. Therefore, the process of the added step S20 will be described below.

[0064] First, after the processing of step S18 described above, since the deterioration trend of the part in the target deterioration data Dd2 is stronger than the deterioration trend of the part in the reference deterioration data Dd10 (step S16: Y), the control change unit 316 performs the following processing (step S20): That is, the control change unit 316 transmits the above-mentioned control content change data Dc (data for vehicle control that reduces the deterioration trend of the part in the target vehicle 2) to the target vehicle 2 (communicator 23).

[0065] After the process of step S20, the process of step S19 is performed. This completes the series of processes shown in Figures 7A and 7B.

[0066] (Actions and Effects) In this modified example, if the predicted deterioration tendency of a part in the target vehicle 2 is stronger than the deterioration tendency of a part in the vehicle fleet 10, as indicated by the reference deterioration data Dd10, the content of the vehicle control executed in the target vehicle 2 is changed, resulting in the following: In other words, since the content of the vehicle control in the target vehicle 2 can be changed in consideration of the predicted result showing a strong deterioration tendency, it is possible to improve convenience.

[0067] Specifically, in this modified example, the content of vehicle control within the target vehicle 2 is changed so as to achieve vehicle control that reduces the tendency for parts to deteriorate (delays deterioration of parts) in the target vehicle 2, resulting in the following: By changing the content of vehicle control in this way, it is possible to reduce the tendency for parts to deteriorate in the target vehicle 2, thereby further improving convenience.

[0068] <Other Modifications> Although an example of an embodiment and modifications of the present disclosure have been described above with reference to the accompanying drawings, the present disclosure is by no means limited to the above-described embodiment. Those skilled in the art will understand that various modifications and variations can be made without departing from the scope defined by the appended claims. The present disclosure is intended to encompass such various modifications and variations to the extent that they fall within the scope of the appended claims and their equivalents.

[0069] For example, the configuration (type, arrangement, number, etc.) of each component in the information processing device 3, 3A, vehicle group 10 (plurality of reference vehicles 1), target vehicle 2, etc. is not limited to that described in the above embodiment, etc. In other words, the configuration of each of these components may be of a different type, arrangement, number, etc. Furthermore, the values, ranges, magnitude relationships, etc. of the various parameters described in the above embodiment, etc. are not limited to those described in the above embodiment, etc., and may be other values, ranges, magnitude relationships, etc.

[0070] In the above embodiment and the like, the process (processing for predicting the deterioration tendency of a part) performed by the information processing device 3, 3A has been described using specific examples, but the process is not limited to these specific examples. That is, for example, the process for predicting the deterioration tendency of a part may be performed using other methods.

[0071] Furthermore, in the above embodiment and the like, specific examples have been given of the content of the notification to the user 9 (information device 90) of the target vehicle 2, but the content of the notification is not limited to these specific examples. That is, for example, the content of the notification may not be changed depending on the magnitude of the deterioration trend, the deterioration cause, the contribution rate, etc., as described above.

[0072] In addition, the series of processes described in the above embodiments may be performed by hardware (circuits), software (programs), or a combination of hardware and software. When performed by software, the software is composed of a group of programs for causing a computer to execute each function. Each program may be, for example, pre-installed in the computer, or may be installed on the computer from a network or recording medium.

[0073] Furthermore, the various examples described above may be applied in any combination.

[0074] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0075] The present disclosure may also be configured as follows: (1) An information processing system comprising: a plurality of reference vehicles belonging to a predetermined vehicle group; a target vehicle that is a vehicle different from the plurality of reference vehicles; and an information processing device configured to predict a deterioration trend over time for parts included in the target vehicles, wherein the information processing device has: a first acquisition unit configured to collect part deterioration data indicating a correspondence between the degree of deterioration of the part and a temporal factor for each part included in the plurality of reference vehicles, and to acquire an aggregate of the part deterioration data for the plurality of reference vehicles as reference deterioration data, a second acquisition unit configured to acquire the part deterioration data for the target vehicle as target deterioration data, and a prediction unit configured to predict the deterioration trend for the part included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit. (2) The information processing system according to (1) above, wherein the information processing device further includes a notification unit configured to provide a predetermined notification to a user of the target vehicle when the deterioration trend of the target vehicle predicted by the prediction unit is stronger than the deterioration trend of the vehicle fleet indicated by the reference deterioration data. (3) The information processing system according to (2) above, wherein the notification unit is configured to change content of the notification depending on the magnitude of the deterioration trend of the target vehicle. (4) The information processing system according to (2) or (3) above, wherein the information processing device further includes an estimation unit configured to estimate one or more deterioration factors and a contribution rate for each of the deterioration factors for the parts included in the target vehicle, and the notification unit is configured to change content of the notification depending on the deterioration factor and the contribution rate estimated by the estimation unit.(5) The information processing system according to any of (1) to (4), wherein the information processing device further includes a control change unit configured to change a content of vehicle control executed in the target vehicle when the deterioration trend in the target vehicle predicted by the prediction unit is stronger than the deterioration trend in the vehicle fleet indicated by the reference deterioration data. (6) The information processing system according to (5), wherein the control change unit is configured to change a content of vehicle control executed in the target vehicle so as to achieve the vehicle control that weakens the deterioration trend in the target vehicle. (7) The information processing system according to any of (1) to (6), wherein the information processing device further includes an information provision unit configured to provide vehicle maintenance information including the prediction result of the deterioration trend for the part to a user of the target vehicle. (8) An apparatus configured to predict the deterioration trend over time of a part included in a target vehicle, which is a vehicle different from a plurality of reference vehicles belonging to a predetermined vehicle group, comprising: a first acquisition unit configured to collect part deterioration data indicating a correspondence between the degree of deterioration of the part and a temporal factor for each part included in the plurality of reference vehicles, and to acquire a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data; a second acquisition unit configured to acquire the part deterioration data for the target vehicle as target deterioration data; and a prediction unit configured to predict the deterioration trend of the part included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit.(9) A method for predicting the deterioration trend over time of a part included in a target vehicle, which is a vehicle different from a plurality of reference vehicles belonging to a predetermined vehicle group, comprising: collecting part deterioration data indicating a correspondence between the degree of deterioration of the part and a time-varying factor for each part included in each of the plurality of reference vehicles, and acquiring a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data; acquiring the part deterioration data for the target vehicle as target deterioration data; and predicting the deterioration trend of the part included in the target vehicle by comparing the reference deterioration data with the target deterioration data.

[0076] The vehicle control unit 21 shown in FIGS. 1, 2, and 6, the information processing unit 31 shown in FIGS. 1 and 2, and the information processing unit 31A shown in FIG. 6 can each be implemented by a circuit including at least one semiconductor integrated circuit, such as at least one processor (e.g., a central processing unit (CPU)), at least one application-specific integrated circuit (ASIC), and / or at least one field-programmable gate array (FPGA). The at least one processor can be configured to execute all or part of the various functions of the vehicle control unit 21 shown in FIGS. 1, 2, and 6, the information processing unit 31 shown in FIGS. 1 and 2, and the information processing unit 31A shown in FIG. 6 by reading instructions from at least one non-transitory, tangible computer-readable medium. Such media can take various forms, including, but not limited to, various magnetic media such as hard disks, various optical media such as CDs or DVDs, and various semiconductor memories (i.e., semiconductor circuits) such as volatile or non-volatile memories. Volatile memory can include DRAM and SRAM. Non-volatile memory can include ROM and NVRAM. An ASIC is an integrated circuit (IC) specialized to execute all or part of the various functions of the vehicle control unit 21 shown in Figures 1, 2 and 6, the information processing unit 31 shown in Figures 1 and 2, and the information processing unit 31A shown in Figure 6. An FPGA is an integrated circuit designed to be configurable after manufacture to execute all or part of the various functions of the vehicle control unit 21 shown in Figures 1, 2 and 6, the information processing unit 31 shown in Figures 1 and 2, and the information processing unit 31A shown in Figure 6.

Claims

1. An information processing system comprising: a plurality of reference vehicles belonging to a predetermined vehicle group; a target vehicle which is a vehicle different from the plurality of reference vehicles; and an information processing device configured to predict the deterioration trend over time of parts included in the target vehicles, wherein the information processing device has: a first acquisition unit configured to collect part deterioration data indicating a correspondence between the degree of deterioration of the parts and temporal factors for each part included in the plurality of reference vehicles, and to acquire a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data; a second acquisition unit configured to acquire the part deterioration data for the target vehicle as target deterioration data; and a prediction unit configured to predict the deterioration trend of the parts included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit.

2. The information processing system of claim 1, further comprising a notification unit configured to provide a predetermined notification to a user of the target vehicle when the deterioration trend in the target vehicle predicted by the prediction unit is stronger than the deterioration trend in the vehicle fleet indicated by the reference deterioration data.

3. The information processing system according to claim 2, wherein the notification unit is configured to change the content of the notification depending on the degree of the deterioration tendency in the target vehicle.

4. The information processing system of claim 2, wherein the information processing device further has an estimation unit configured to estimate one or more deterioration factors and the contribution rate of each of the deterioration factors for the parts included in the target vehicle, and the notification unit is configured to change the content of the notification depending on the deterioration factors and the contribution rates estimated by the estimation unit.

5. The information processing system of any one of claims 1 to 4, further comprising a control change unit configured to change the content of vehicle control executed in the target vehicle when the deterioration trend in the target vehicle predicted by the prediction unit is stronger than the deterioration trend in the vehicle group indicated by the reference deterioration data.

6. The information processing system according to claim 5, wherein the control change unit is configured to change the content of the vehicle control executed in the target vehicle so that the vehicle control reduces the deterioration tendency in the target vehicle.

7. An information processing system as described in any one of claims 1 to 4, wherein the information processing device further has an information providing unit configured to provide vehicle maintenance information including the predicted results of the deterioration tendency for the parts to a user of the target vehicle.

8. An apparatus configured to predict the deterioration trend over time of a part included in a target vehicle which is a vehicle different from a plurality of reference vehicles belonging to a predetermined vehicle group, comprising: a first acquisition unit configured to collect part deterioration data indicating a correspondence between the degree of deterioration of the part and temporal factors for each part included in each of the plurality of reference vehicles, and to acquire a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data; a second acquisition unit configured to acquire the part deterioration data for the target vehicle as target deterioration data; and a prediction unit configured to predict the deterioration trend of the part included in the target vehicle by comparing the reference deterioration data acquired by the first acquisition unit with the target deterioration data acquired by the second acquisition unit.

9. A method for predicting the deterioration trend over time of a part included in a target vehicle which is a vehicle different from a plurality of reference vehicles belonging to a specified vehicle group, comprising: collecting part deterioration data indicating a correspondence between the degree of deterioration of the part and a time-dependent factor for each part included in each of the plurality of reference vehicles, and acquiring a collection of the part deterioration data for the plurality of reference vehicles as reference deterioration data; acquiring the part deterioration data for the target vehicle as target deterioration data; and predicting the deterioration trend of the part included in the target vehicle by comparing the reference deterioration data with the target deterioration data.

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