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

Abstract

An information processing device 10 comprises a control unit 13 that: acquires first speed data in which the speed of a vehicle 20 changes over time in a first cycle; acquires correction data in which a speed-related parameter, which varies according to the speed in the acquired first speed data, changes over time; and corrects the first speed data on the basis of the correction data to acquire second speed data in which the speed changes over time in a second cycle which is shorter than the first cycle.

Description

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

[0001] The present disclosure relates to an information processing device, an information processing system, a program, and an information processing method.

[0002] Conventionally, techniques for predicting the durability state of tires mounted on a vehicle have been known. For example, Patent Document 1 discloses a tire durability performance prediction method that can easily predict the durability performance of a tire in a short period of time. Generally, in order to predict the durability state of a tire, the history of vehicle driving information is important. For example, vehicle speed information is highly important.

[0003] Japanese Patent Application Laid-Open No. 2008-256442

[0004] On the other hand, a large storage capacity is required for an information processing device such as a server to periodically acquire and store the speed information history. In addition, communication costs are incurred when transmitting and receiving the acquired speed information between the vehicle and the information processing device. A shorter update frequency of the speed information is preferable for predicting the tire's durability. Conversely, from the perspective of data communication and data storage, a longer update frequency of the speed information is preferable. The accuracy of tire durability prediction and the acquisition costs based on data communication and data storage do not contradict each other as the update frequency increases or decreases, but rather change in the same direction. Therefore, it has not been easy to determine an appropriate balance between prediction accuracy and acquisition costs.

[0005] The present disclosure provides a technique that can appropriately determine the balance between the accuracy of predicting the durability state of a tire and the cost of acquiring speed information.

[0006] An information processing device according to one embodiment of the present disclosure includes: (1) a control unit that acquires first speed data in which the speed of a vehicle changes over time in a first period, acquires correction data in which a speed-related parameter in the acquired first speed data, which has a variation according to the speed, changes over time, and corrects the first speed data based on the correction data to acquire second speed data in which the speed changes over time in a second period shorter than the first period.

[0007] (2) In the information processing device described in (1) above, the control unit may acquire actual measurement data in advance using a measurement vehicle, the actual measurement data including the speed that changes over time in the second period and the acceleration corresponding to the speed, and perform preprocessing based on the acquired actual measurement data.

[0008] (3) In the information processing device according to (2), in the preprocessing, the control unit may calculate a frequency distribution of the speed-related parameter for each average speed over the first period of the speed in the actual measurement data.

[0009] (4) In the information processing device according to (3), in the preprocessing, the control unit may calculate the variation in the speed-related parameter for each of the average speeds based on the frequency distribution.

[0010] (5) In the information processing device described in any one of (2) to (4) above, the control unit may generate the first speed data by calculating the speed in the first period based on vehicle travel information acquired from the vehicle.

[0011] (6) In the information processing device according to any one of (2) to (5), the control unit may generate the second speed data by adding the speed-related parameter that changes over time in the correction data to the speed in the first speed data.

[0012] (7) In the information processing device described in (6) above, the control unit may generate the correction data by randomly varying the speed-related parameter over time within a range of the variation calculated in the preprocessing that corresponds to the speed in the first speed data.

[0013] (8) In the information processing device according to any one of (1) to (7), the speed-related parameters may include acceleration.

[0014] (9) In the information processing device according to any one of (1) to (8) above, the control unit may predict a durability state of tires of the vehicle based on the acquired second speed data.

[0015] An information processing system according to an embodiment of the present disclosure includes: (10) the information processing device according to any one of (1) to (9) above; and the vehicle that provides driving information of the vehicle to the information processing device.

[0016] A program according to one embodiment of the present disclosure (11) causes an information processing device to perform operations including: acquiring first speed data in which the speed of a vehicle changes over time in a first period; acquiring correction data in which a speed-related parameter in the acquired first speed data, which has a variation according to the speed, changes over time; and acquiring second speed data in which the speed changes over time in a second period shorter than the first period by correcting the first speed data based on the correction data.

[0017] An information processing method according to one embodiment of the present disclosure (12) is an information processing method executed in an information processing device, comprising: acquiring first speed data in which the speed of a vehicle changes over time in a first period; acquiring correction data in which a speed-related parameter in the acquired first speed data, which has a variation according to the speed, changes over time; and correcting the first speed data based on the correction data to acquire second speed data in which the speed changes over time in a second period shorter than the first period.

[0018] According to an information processing device, an information processing system, a program, and an information processing method according to an embodiment of the present disclosure, it is possible to appropriately determine a balance between the prediction accuracy of the tire durability state and the cost of acquiring speed information.

[0019] 1 is a configuration diagram showing a configuration of an information processing system including an information processing device according to an embodiment of the present disclosure. FIG. 2 is a block diagram showing a schematic configuration of each of the information processing device and a vehicle of FIG. 1. FIG. 3 is a flowchart for explaining a first example of an information processing method executed by the information processing device of FIG. 1. FIG. 4 is a flowchart for explaining an example of a process executed by the information processing device of FIG. 1. FIG. 5 is a diagram for explaining an example of a process executed by the information processing device of FIG. 1. FIG. 6 is a diagram for explaining an example of a process executed by the information processing device of FIG. 1. FIG. 7 is a diagram for explaining an example of a process executed by the information processing device of FIG. 1.

[0020] An embodiment of the present disclosure will be mainly described below with reference to the accompanying drawings. The following description also applies to an information processing system 1 including an information processing device 10, to which the present disclosure is applied, and an information processing method and program executed by the information processing device 10.

[0021] 1 is a configuration diagram showing the configuration of an information processing system 1 including an information processing device 10 according to an embodiment of the present disclosure. An overview of the information processing system 1 including the information processing device 10 according to an embodiment of the present disclosure will be mainly described with reference to FIG. 1. The information processing system 1 includes a vehicle 20 in addition to the information processing device 10.

[0022] For ease of explanation, only one information processing device 10 is illustrated in Fig. 1 , but the information processing system 1 may have two or more information processing devices 10. Similarly, only one vehicle 20 is illustrated in Fig. 1 , but the information processing system 1 may have two or more vehicles 20. Each of the information processing device 10 and the vehicle 20 is communicatively connected to a network 30 including a mobile communication network and the Internet. Either the information processing device 10 or the vehicle 20 is communicatively connected to another device via the network 30.

[0023] The information processing device 10 is, for example, one or more server devices that can communicate with each other. The information processing device 10 is not limited to these, and may be any general-purpose electronic device such as a PC (Personal Computer) or a smartphone, or may be another electronic device dedicated to the information processing system 1.

[0024] The vehicle 20 is, for example, any vehicle equipped with tires and capable of running by an operating engine. The vehicle 20 is, for example, an automobile, but is not limited to this. Automobiles include gasoline-powered automobiles, electric automobiles, hybrid automobiles, plug-in hybrid automobiles, and fuel cell automobiles. The vehicle 20 may be driven by a driver, or may be automated at any automation level. The automation level may be, for example, any of levels 1 to 5 in the SAE (Society of Automotive Engineers) classification.

[0025] In one embodiment, the information processing device 10 acquires first speed data in which the speed of the vehicle 20 changes over time in a first period. In the present disclosure, the "first period" includes, for example, a period in which the information processing device 10 acquires the speed of the vehicle 20 as information at a low frequency. The first period may be, but is not limited to, 180 seconds as one example value.

[0026] The information processing device 10 acquires correction data. In the correction data, a speed-related parameter having a variance according to the speed in the acquired first speed data changes over time. In the present disclosure, the "speed-related parameter" includes, for example, acceleration. The acceleration includes, for example, forward and backward acceleration along the traveling direction of the vehicle 20. The "variance" includes, for example, standard deviation.

[0027] The information processing device 10 corrects the first speed data based on the acquired correction data to acquire second speed data in which the speed changes over time at a second period shorter than the first period. In the present disclosure, the "second period" includes, for example, a period when the information processing device 10 frequently generates the speed of the vehicle 20 as information. The second period may be, but is not limited to, one second as an example value.

[0028] Fig. 2 is a block diagram showing a schematic configuration of each of the information processing device 10 and the vehicle 20 in Fig. 1. With reference to Fig. 2, an example of the configuration of each of the information processing device 10 and the vehicle 20 included in the information processing system 1 will be mainly described.

[0029] As shown in FIG. 2, the information processing device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0030] The communication unit 11 includes one or more communication interfaces connected to the network 30. The communication interfaces are compatible with, for example, mobile communication standards such as 4G (4th Generation) and 5G (5th Generation), wired LAN (Local Area Network) standards, or wireless LAN standards, but are not limited to these and may be compatible with any communication standard. For example, the communication interface may also be compatible with a short-range wireless communication standard. In one embodiment, the information processing device 10 is communicatively connected to the network 30 via the communication unit 11. The communication unit 11 transmits and receives various information via the network 30.

[0031] The storage unit 12 includes storage modules such as a hard disk drive (HDD), a solid state drive (SSD), an electrically erasable programmable read-only memory (EEPROM), a read-only memory (ROM), and a random access memory (RAM). The storage unit 12 stores information necessary to realize the operation of the information processing device 10. The storage unit 12 stores information obtained by the operation of the information processing device 10. For example, the storage unit 12 stores system programs, application programs, and various data obtained by any means such as communication.

[0032] The storage unit 12 may function as a main storage module, an auxiliary storage module, or a cache memory. The storage unit 12 is not limited to being built into the information processing device 10, and may include an external storage module connected via a digital input / output port such as a USB (Universal Serial Bus).

[0033] The control unit 13 includes one or more processors. In the present disclosure, a "processor" refers to, but is not limited to, a general-purpose processor or a dedicated processor specialized for a specific process. The control unit 13 includes, for example, a CPU (Central Processing Unit). The control unit 13 is communicably connected to each component of the information processing device 10 and controls the operation of the information processing device 10 as a whole.

[0034] 2, the vehicle 20 includes a communication unit 21, a storage unit 22, an acquisition unit 23, and a control unit 24. The communication unit 21, the storage unit 22, the acquisition unit 23, and the control unit 24 are connected to each other so as to be able to communicate with each other via an in-vehicle network such as a Controller Area Network (CAN) or a dedicated line.

[0035] The communication unit 21 includes one or more communication interfaces connected to the network 30. The communication interfaces are compatible with mobile communication standards such as 4G and 5G, or wireless LAN standards, but may be compatible with any communication standard without being limited thereto. For example, the communication interfaces may be compatible with short-range wireless communication standards. In one embodiment, the vehicle 20 is communicatively connected to the network 30 via the communication unit 21. The communication unit 21 transmits and receives various information via the network 30.

[0036] The storage unit 22 includes storage modules such as an HDD, an SSD, an EEPROM, a ROM, and a RAM. The storage unit 22 stores information necessary to realize the operation of the vehicle 20. The storage unit 22 stores information obtained by the operation of the vehicle 20. For example, the storage unit 22 stores system programs, application programs, and various data acquired by any means such as communication.

[0037] The storage unit 22 may function as a main storage module, an auxiliary storage module, or a cache memory. The storage unit 22 is not limited to being built into the vehicle 20, and may include an external storage module connected via a digital input / output port such as a USB.

[0038] The acquisition unit 23 includes one or more receivers compatible with any satellite positioning system. The receiver includes, for example, a Global Navigation Satellite System (GNSS) receiver such as a Global Positioning System (GPS) receiver. The acquisition unit 23 acquires measurement values ​​of the position of the vehicle 20 as position information. The position information includes, for example, an address, latitude, longitude, and altitude. The acquisition unit 23 may acquire the position information of the vehicle 20 continuously, periodically, or irregularly. The acquisition unit 23 may complement the position information by using information on the vehicle speed pulse of the vehicle 20 and other information based on autonomous navigation.

[0039] The control unit 24 includes one or more processors. The control unit 24 includes, for example, an ECU (Electronic Control Unit). The control unit 24 is communicably connected to each component of the vehicle 20 and controls the operation of the entire vehicle 20.

[0040] Fig. 3 is a flowchart for explaining a first example of an information processing method executed by the information processing device 10 of Fig. 1. The first example of the information processing method executed by the information processing device 10 of Fig. 1 will be mainly explained with reference to Fig. 3. The flowchart shown in Fig. 3 shows the basic processing flow of the information processing method executed by the information processing device 10.

[0041] In step S101, the control unit 13 of the information processing device 10 acquires first speed data in which the speed of the vehicle 20 changes over time in a first cycle. For example, the control unit 24 of the vehicle 20 acquires the traveling position of the vehicle 20 as position information using the acquisition unit 23. The control unit 24 of the vehicle 20 associates the traveling position acquired using the acquisition unit 23 with the traveling time at that time, and generates traveling information. In the present disclosure, "traveling information" includes, for example, the real-time traveling time and traveling position when acquiring speed information for the vehicle 20 whose tire durability state is to be predicted.

[0042] The control unit 24 of the vehicle 20 transmits the generated driving information to the information processing device 10 via the communication unit 21 and the network 30. The control unit 13 of the information processing device 10 receives the driving information generated in the vehicle 20 from the vehicle 20 via the network 30 and the communication unit 11. The control unit 13 of the information processing device 10 generates first speed data based on the acquired driving information in accordance with the flowchart of FIG. 5 , which will be described later, and stores the first speed data in the memory unit 12.

[0043] In step S102, the control unit 13 of the information processing device 10 acquires correction data in which a speed-related parameter having a variation corresponding to the speed in the first speed data acquired in step S101 changes over time. The variation is calculated in preprocessing according to the flowchart in FIG. 4 , which will be described later. For example, the control unit 13 generates correction data by randomly changing the speed-related parameter over time within the range of the variation corresponding to the speed in the first speed data, among the calculated variations. The control unit 13 stores the generated correction data in the storage unit 12.

[0044] In step S103, the control unit 13 of the information processing device 10 corrects the first speed data acquired in step S101 based on the correction data acquired in step S102 to acquire second speed data. In the second speed data, the speed of the vehicle 20 changes over time in a second period that is shorter than the first period. For example, the control unit 13 generates the second speed data by adding a time-varying speed-related parameter in the correction data to the speed of the vehicle 20 in the first speed data. The control unit 13 stores the generated second speed data in the storage unit 12.

[0045] In step S104, the control unit 13 of the information processing device 10 predicts the durability state of the tires of the vehicle 20 based on the second speed data acquired in step S103. For example, the control unit 13 predicts the durability state of the tires of the vehicle 20 according to a known prediction method, using the second speed data as speed information and any other information required for the prediction process, such as tire temperature information.

[0046] 4 is a flowchart for explaining a second example of an information processing method executed by the information processing device 10 of FIG. 1. The second example of the information processing method executed by the information processing device 10 of FIG. 1 will be mainly explained with reference to FIG. 4. The flowchart shown in FIG. 4 shows the flow of pre-processing before the series of processes shown in the flowchart of FIG. 3 are executed. The pre-processing is executed based on past actual measurement data when a vehicle identical to or different from vehicle 20 is used as a test vehicle. The test vehicle is equipped with sensors including a speed sensor and an acceleration sensor that can directly measure the speed, acceleration, etc. of the test vehicle.

[0047] In step S201, the control unit 13 of the information processing device 10 acquires actual measurement data from a test vehicle that has been driven normally. In the present disclosure, "actual measurement data" includes data indicating time changes in speed and acceleration, acquired using the above-described sensors for the test vehicle while it is running. For example, the control unit 13 acquires in advance, using the test vehicle, actual measurement data including the speed that changes over time in the second period and the acceleration corresponding to the speed.

[0048] The control unit 13 may receive actual measurement data generated by the test vehicle itself based on measurements made on the test vehicle from the test vehicle via the network 30 and the communication unit 11. However, this is not limiting, and the control unit 13 may acquire actual measurement data generated by the test vehicle itself from the test vehicle using any data acquisition method that does not involve the network 30. The control unit 13 stores the acquired actual measurement data in the memory unit 12. The control unit 13 performs preprocessing based on the acquired actual measurement data.

[0049] The larger the amount of actual measurement data acquired, the better so that the control unit 13 can accurately perform statistical processing. However, if the amount of data that can be acquired as actual measurement data is limited, for example, a measurement vehicle may travel in locations and along routes where the vehicle 20 is actually scheduled to travel, and the control unit 13 may acquire the actual measurement data obtained by the measurement vehicle at that time.

[0050] In step S202, the control unit 13 of the information processing device 10 calculates the average speed over the first period of the speed in the actual measurement data acquired in step S201.

[0051] In step S203, the control unit 13 of the information processing device 10 calculates a frequency distribution of speed-related parameters for each average speed calculated in step S202.

[0052] In step S204, the control unit 13 of the information processing device 10 calculates the variation of the speed-related parameter for each average speed calculated in step S202 based on the frequency distribution calculated in step S203. In this way, the control unit 13 obtains the relationship between the average speed and the variation as information.

[0053] Fig. 5 is a flowchart for explaining a third example of an information processing method executed by the information processing device 10 of Fig. 1. The third example of the information processing method executed by the information processing device 10 of Fig. 1 will be mainly explained with reference to Fig. 5. The flowchart shown in Fig. 5 more specifically illustrates the process of acquiring first speed data in step S101 of the flowchart of Fig. 3. The control unit 13 of the information processing device 10 generates the first speed data based on the driving information provided to the information processing device 10 from the vehicle 20.

[0054] In step S301, the control unit 13 of the information processing device 10 acquires driving information of the vehicle 20 from the vehicle 20. For example, the control unit 13 receives driving information generated in the vehicle 20 from the vehicle 20 via the network 30 and the communication unit 11. The control unit 13 acquires such driving information from the vehicle 20 in a first cycle. The control unit 13 stores the acquired driving information in the storage unit 12.

[0055] In step S302, the control unit 13 of the information processing device 10 calculates the speed of the vehicle 20 in the first period based on the travel information of the vehicle 20 acquired from the vehicle 20 in step S301. As a result, the control unit 13 generates first speed data. For example, the control unit 13 calculates the average speed of the vehicle 20 over the first period by dividing (difference in travel position) by (difference in corresponding travel time) based on the acquired travel time and travel position.

[0056] In step S303, the control unit 13 of the information processing device 10 stores the first speed data acquired in step S302 in the storage unit 12.

[0057] Thereafter, the control unit 13 of the information processing device 10 executes the processes from step S102 onward in the flowchart of Fig. 3. At this time, the control unit 13 refers to the acceleration variation corresponding to the average speed over the first period calculated in step S302 from the relationship between the average speed and the variation previously acquired in step S204 of the flowchart of Fig. 4. The control unit 13 generates a change in the speed of the vehicle 20 by adding a random acceleration based on the correction data acquired in step S102 of the flowchart of Fig. 3 to the average speed over the first period calculated in step S302. Through this generation process, the control unit 13 acquires second speed data in which the speed of the vehicle 20 changes over time in a second period that is shorter than the first period.

[0058] The pre-processing executed by the control unit 13 of the information processing device 10 according to the flowchart of FIG. 4 will be described in more detail with reference to FIGS. 6 to 8. FIG.

[0059] Fig. 6 is a first diagram for explaining an example of processing executed by the information processing device 10 of Fig. 1. Fig. 6 shows how the control unit 13 calculates the average speed over the first period of the speed in the acquired actual measurement data in steps S201 and S202 of the flowchart of Fig. 4. In Fig. 6, the horizontal axis represents time (s), and the vertical axis represents speed (km / h).

[0060] Of the two graphs shown in Figure 6, the dotted line graph is based on the speed values ​​of actual measurement data that change over time in the second period, which were actually acquired using the above-mentioned sensor on a moving measurement vehicle. In the actual measurement data acquired from the measurement vehicle, the speed is sampled at a high frequency, that is, the second period. Therefore, the dotted line graph shows how the speed changes sharply and smoothly over time in response to the high-frequency data sampling.

[0061] Of the two graphs shown in Figure 6, the solid line graph is based on the average speed value over the first period of the acquired actual measurement data. The solid line graph is the result of averaging the dotted line graph based on the first period. The speed, which was sampled at a high frequency in the second period in the actual measurement data acquired from the measurement vehicle, changes less frequently over time based on the averaging process over the first period. Therefore, the solid line graph is flat over the first period, indicating that the speed remains constant over the first period.

[0062] FIG. 7 is a second diagram for explaining an example of processing executed by the information processing device 10 of FIG. 1. FIG. 7 shows the frequency distribution of speed-related parameters calculated for each average speed shown by the solid line graph in FIG. 6 in accordance with step S203 of the flowchart in FIG. 4. In FIG. 7, the horizontal axis represents acceleration (m / s ２ 7, acceleration is shown as an example of a speed-related parameter. The vertical axis indicates the frequency rate in the frequency distribution.

[0063] Each of the multiple solid line graphs shown in Fig. 7 corresponds to one of the multiple average velocities shown by the solid line graphs in Fig. 6. Each of the solid line graphs is a histogram of the acceleration variation corresponding to each average velocity.

[0064] FIG. 8 is a third diagram for explaining an example of processing executed by the information processing device 10 of FIG. 1. FIG. 8 shows how the control unit 13 acquires the relationship between the average speed and the variation as information in accordance with step S204 of the flowchart of FIG. 4. In FIG. 8, the horizontal axis represents the speed (m / s). The speed (m / s) corresponds to the average speed shown by the solid line graph in FIG. 6. The vertical axis represents the standard deviation (m / s ２ ) is shown.

[0065] The variance of the speed-related parameter, i.e., the standard deviation, is calculated for each average speed indicated by the solid line graph in Fig. 6 based on the frequency distribution shown in Fig. 7. In Fig. 8, the black dots indicate how the variance of the speed-related parameter changes depending on the average speed. As an example, the variance of the speed-related parameter tends to decrease as the average speed increases.

[0066] The dotted line in Figure 8 is an approximation line for the variation of the speed-related parameters indicated by the black circles. The approximation line is expressed, for example, by a quadratic function. The time dependency of the variation of the speed-related parameters indicated by the black circles is expressed by an approximation line that monotonically decreases in a quadratic function as the average speed increases. The control unit 13 of the information processing device 10 calculates such an approximation line showing the relationship between the average speed and the variation in preprocessing and stores it in advance in the storage unit 12.

[0067] The process of acquiring the second speed data executed by the control unit 13 of the information processing device 10 according to the flowchart of FIG. 3 will be described in more detail with reference to FIGS. 9 to 12. FIG.

[0068] 9 is a fourth diagram for explaining an example of processing executed by the information processing device 10 of FIG. 1. FIG. 9 shows the time dependency of the speed in the first speed data acquired in step S101 of the flowchart of FIG. 3 for only a portion of the time period. In FIG. 9, the horizontal axis represents time (s), and the vertical axis represents speed (m / s).

[0069] As described above with reference to the flowchart of Fig. 5, in the first speed data, the speed of the vehicle 20 is the average speed over the first period. Therefore, in Fig. 9, the speed of the vehicle 20 is constant over the first period.

[0070] FIG. 10 is a fifth diagram for explaining an example of processing executed by the information processing device 10 of FIG. 1. FIG. 10 shows the time dependency of acceleration in the correction data acquired in step S102 of the flowchart of FIG. 3 for only a portion of the time period. In FIG. 10, the horizontal axis represents time (s). The vertical axis represents acceleration (m / s ２ ) is shown.

[0071] The control unit 13 of the information processing device 10 refers to the variation in acceleration corresponding to the speed in the first speed data shown in Fig. 9 from the relationship between the average speed and variation shown in Fig. 8. The control unit 13 generates correction data as shown in Fig. 10 in which the acceleration having the referenced variation changes over time. The control unit 13 generates the correction data by randomly changing the acceleration over time within the range of the referenced variation.

[0072] In this case, the random acceleration generated in the correction data is not uniformly random, but is based on randomness according to variation. For example, the control unit 13 randomly varies the acceleration over time according to a normal distribution while referring to the frequency distribution of acceleration obtained for the corresponding average speed in Figure 7. The distance between the pair of dotted lines shown vertically in Figure 10 corresponds to the width of the normal distribution. The control unit 13 generates correction data by randomly varying the acceleration over time within the range of the normal distribution.

[0073] Fig. 11 is a sixth diagram illustrating an example of processing executed by the information processing device 10 of Fig. 1. Fig. 11 shows the time dependency of the speed in the second speed data acquired in step S103 of the flowchart of Fig. 3 for only a portion of the time period. In Fig. 11, the horizontal axis represents time (s), and the vertical axis represents speed (m / s).

[0074] The control unit 13 of the information processing device 10 acquires second speed data by adding the acceleration that changes over time in the correction data to the speed of the vehicle 20 in the first speed data. For example, the control unit 13 changes the speed of the vehicle 20 in the first speed data over time in accordance with the acceleration that changes over time in the correction data. The acceleration of the correction data that changes over time frequently based on a second period that is shorter than the first period is added to the speed of the vehicle 20 in the first speed data, so that in the second speed data, the speed of the vehicle 20 changes over time with the second period that is shorter than the first period.

[0075] Fig. 12 is a seventh diagram for explaining an example of processing executed by the information processing device 10 of Fig. 1. Fig. 12 compares the second speed data acquired in step S103 of the flowchart of Fig. 3 with actual measurement data of the speed of the vehicle 20, which changes over time with high frequency in a second cycle. In Fig. 12, the horizontal axis represents time (s), and the vertical axis represents speed (km / h).

[0076] 12, the dotted line graph shows actual measurement data of the speed of the vehicle 20, which changes over time at a high frequency in the second period. In this actual measurement data, the speed is sampled at the high frequency of the second period. Therefore, the dotted line graph shows how the speed changes sharply and smoothly over time in accordance with the high-frequency data sampling.

[0077] Of the two graphs shown in Fig. 12, the solid line graph represents the second speed data acquired in step S103 of the flowchart in Fig. 3. Unlike the solid line graph in Fig. 6, which is averaged over the first period, the solid line graph represents the time change in the speed of the vehicle 20 over a second period that is shorter than the first period. The solid line graph closely matches the time change trend of the dotted line graph. Therefore, the process of acquiring the second speed data executed by the information processing device 10 in Fig. 1 functions with high accuracy.

[0078] According to the embodiment described above, it is possible to appropriately determine the balance between the prediction accuracy of the tire durability state and the cost of acquiring speed information. The information processing device 10 corrects the first speed data based on the correction data to acquire second speed data in which the speed changes over time at a second period shorter than the first period. This allows the information processing device 10 to estimate speed using the second speed data with the same accuracy as when the speed information is updated more frequently, while reducing the cost of acquiring speed information.

[0079] The information processing device 10 acquires in advance, using a measurement vehicle, actual measurement data including a speed that changes over time in a second period and an acceleration corresponding to the speed, and performs preprocessing based on the acquired actual measurement data. This allows the information processing device 10 to acquire in advance, before estimating the speed of the vehicle 20 using the second speed data, information necessary for generating correction data for calculating second speed data from first speed data in which the speed of the vehicle 20 changes over time in a first period. For example, the information processing device 10 can acquire information regarding the relationship between average speed and variation.

[0080] In the preprocessing, the information processing device 10 calculates the frequency distribution of the speed-related parameter for each average speed over the first period of the speed in the actual measurement data. This allows the information processing device 10 to accurately obtain information on the relationship between the average speed and the variation required to generate correction data in advance before estimating the speed of the vehicle 20 using the second speed data.

[0081] In the preprocessing, the information processing device 10 calculates the variation of the speed-related parameter for each average speed based on the frequency distribution. This allows the information processing device 10 to accurately obtain information on the relationship between the average speed and the variation, which is necessary for generating correction data, in advance before estimating the speed of the vehicle 20 using the second speed data.

[0082] The information processing device 10 generates first speed data by calculating the speed in the first period based on the driving information of the vehicle 20 acquired from the vehicle 20. This allows the information processing device 10 to generate the first speed data simply by acquiring driving information at a low frequency from the vehicle 20 that has only the original configuration required for driving, thereby reducing communication costs between the vehicle 20 and the information processing device 10.

[0083] The information processing device 10 acquires second speed data by adding a time-varying speed-related parameter in the correction data to the speed in the first speed data. This allows the information processing device 10 to acquire second speed data with high accuracy from the first speed data, whose speed changes over time infrequently according to the first period. The information processing device 10 can estimate a speed using the second speed data with the same accuracy as when the speed information is updated more frequently, while reducing the cost of acquiring speed information.

[0084] The information processing device 10 generates correction data by randomly varying the speed-related parameters over time within a range of variation corresponding to the speed in the first speed data, among the variations calculated in the preprocessing. This allows the information processing device 10 to accurately acquire data of the speed-related parameters that plausibly match the speed in the first speed data as correction data. As a result, the information processing device 10 can acquire second speed data with higher accuracy from the first speed data, in which the speed changes over time with low frequency due to the first period.

[0085] The speed-related parameters include acceleration. This allows the information processing device 10 to generate second speed data that exhibits appropriate time changes without excessively rapid acceleration, compared to, for example, generating second speed data by directly adding speed variations to the average speed of the vehicle 20 in the first speed data. Therefore, the information processing device 10 can acquire second speed data with higher accuracy from first speed data in which the speed changes over time infrequently due to the first period.

[0086] Based on the acquired second speed data, the information processing device 10 predicts the durability state of the tires of the vehicle 20. This allows the information processing device 10 to accurately predict the durability state of the tires of the vehicle 20 based on the second speed data acquired with high accuracy as described above.

[0087] Although the present disclosure has been described based on the drawings and examples, it should be noted that those skilled in the art can make various modifications and changes based on the present disclosure. Therefore, it should be noted that these modifications and changes are included in the scope of the present disclosure. For example, the functions included in each configuration or step can be rearranged so as not to be logically inconsistent, and multiple configurations or steps can be combined or divided into one.

[0088] For example, a general-purpose electronic device such as a smartphone or a computer can be configured to function as the information processing device 10 according to the embodiment. Specifically, a program describing the processing content for realizing each function of the information processing device 10 according to the embodiment is stored in the memory of the electronic device, and the program is read and executed by a processor of the electronic device. Therefore, the present disclosure can also be realized as a program executable by a processor.

[0089] Alternatively, the present disclosure may be realized as a non-transitory computer-readable medium storing a program executable by one or more processors to cause the information processing device 10 according to an embodiment to execute each function, etc. It should be understood that these are also included within the scope of the present disclosure.

[0090] For example, at least a part of the processing operations executed in the information processing device 10 in the above-described embodiment may be executed in the vehicle 20. For example, instead of the information processing device 10, the vehicle 20 itself may execute the above-described series of processing operations related to the information processing device 10. At least a part of the processing operations executed in the vehicle 20 may be executed in the information processing device 10.

[0091] The information processing device 10 and the vehicle 20 do not need to be communicatively connected to each other via the network 30. For example, the information processing device 10 may be mounted on the vehicle 20 and communicatively connected directly to the vehicle 20 without going through the network 30.

[0092] In the above embodiment, the information processing device 10 acquires actual measurement data including the velocity that changes over time in the second period and the acceleration corresponding to the velocity in advance using a measurement vehicle, and performs preprocessing based on the acquired actual measurement data. However, this is not limited to this. The information processing device 10 does not have to perform such preprocessing. In this case, the information processing device 10 may generate correction data by acquiring information on the relationship between the average velocity and the variation from any other external device.

[0093] In the above embodiment, the information processing device 10 calculates the frequency distribution of the speed-related parameters for each average speed over the first period of the speed in the actual measurement data in the preprocessing. However, this is not limited to this. The information processing device 10 does not need to perform such calculation processing in the preprocessing. The information processing device 10 may perform any other calculation processing that can acquire information necessary for generating correction data in advance.

[0094] In the above embodiment, the information processing device 10 calculates the variation of the speed-related parameters for each average speed based on the frequency distribution in the preprocessing. However, this is not limited to this. The information processing device 10 does not need to perform such calculation processing in the preprocessing. The information processing device 10 may perform any other calculation processing that can acquire information necessary for generating correction data in advance.

[0095] In the above embodiment, the information processing device 10 generates the first speed data by calculating the speed in the first period based on the traveling information of the vehicle 20 acquired from the vehicle 20, but this is not limited to this. The information processing device 10 may generate the first speed data by directly acquiring speed information from the vehicle 20 instead of or in addition to the traveling information. In this case, the information processing device 10 may receive the speed information generated in the vehicle 20 from the vehicle 20 in the first period via the network 30 and the communication unit 11.

[0096] In the above embodiment, the information processing device 10 generates the second speed data by adding a time-varying speed-related parameter in the correction data to the speed in the first speed data, but this is not limiting. The information processing device 10 may acquire the second speed data by performing any other process instead of or in addition to such a generation process.

[0097] In the above embodiment, the information processing device 10 generates the correction data by randomly varying the speed-related parameters over time within the range of variation corresponding to the speed in the first speed data among the variations calculated in the preprocessing. However, the information processing device 10 is not limited to this. Instead of or in addition to such a generation process, the information processing device 10 may acquire the correction data by executing any other process.

[0098] In the above embodiment, the speed-related parameter includes acceleration, but is not limited to this. The speed-related parameter may include the speed itself.

[0099] In the above embodiment, the information processing device 10 predicts the durability state of the tires of the vehicle 20 based on the acquired second speed data, but this is not limiting. The information processing device 10 does not have to perform such a prediction process. The prediction process of the durability state of the tires of the vehicle 20 based on the second speed data may be performed by any other external device instead of the information processing device 10.

[0100] In the above embodiment, the approximation line shown in Fig. 8 is described as being expressed by a quadratic function, but is not limited to this. The approximation line may be expressed by a higher-order function or a linear function.

[0101] In the above embodiment, the information processing device 10 has been described as acquiring from the vehicle 20 driving information generated by associating the driving position with the driving time in the vehicle 20, but this is not limited to this. The information processing device 10 may acquire only driving position information from the vehicle 20 and generate the driving information within the information processing device 10 itself. In this case, the information processing device 10 may acquire the time when only the driving position information was acquired from the vehicle 20 from information held within the information processing device 10 itself, or may acquire it from an arbitrary external device via the network 30 and the communication unit 11.

[0102] According to the present disclosure, it is possible to provide an information processing device, an information processing system, a program, and an information processing method that can appropriately determine the balance between the prediction accuracy of the durability state of a tire and the cost of acquiring speed information.

[0103] REFERENCE SIGNS LIST 1 Information processing system 10 Information processing device 11 Communication unit 12 Storage unit 13 Control unit 20 Vehicle 21 Communication unit 22 Storage unit 23 Acquisition unit 24 Control unit 30 Network

Claims

1. An information processing device comprising: a control unit that acquires first speed data in which a vehicle's speed changes over time in a first period, acquires correction data in which a speed-related parameter in the acquired first speed data, which has a variation according to the speed, changes over time, and corrects the first speed data based on the correction data to acquire second speed data in which the speed changes over time in a second period shorter than the first period.

2. An information processing device according to claim 1, wherein the control unit acquires in advance actual measurement data including the speed which changes over time in the second period and the acceleration corresponding to the speed using a measurement vehicle, and performs pre-processing based on the acquired actual measurement data.

3. An information processing device according to claim 2, wherein the control unit, in the pre-processing, calculates a frequency distribution of the speed-related parameter for each average speed over the first period of the speed in the actual measurement data.

4. An information processing device according to claim 3, wherein the control unit, in the pre-processing, calculates the variance of the speed-related parameter for each of the average speeds based on the frequency distribution.

5. An information processing device according to any one of claims 2 to 4, wherein the control unit generates the first speed data by calculating the speed in the first period based on vehicle travel information acquired from the vehicle.

6. An information processing device according to any one of claims 2 to 4, wherein the control unit generates the second speed data by adding the speed-related parameter that changes over time in the correction data to the speed in the first speed data.

7. An information processing device according to claim 6, wherein the control unit generates the correction data by randomly varying the speed-related parameter over time within a range of the variation calculated in the pre-processing that corresponds to the speed in the first speed data.

8. An information processing device according to any one of claims 1 to 4, wherein the speed-related parameter includes acceleration.

9. An information processing device according to any one of claims 1 to 4, wherein the control unit predicts a durability state of tires of the vehicle based on the acquired second speed data.

10. An information processing system comprising: an information processing device according to any one of claims 1 to 4; and a vehicle that provides driving information of the vehicle to the information processing device.

11. A program that causes an information processing device to perform operations including: acquiring first speed data in which the speed of a vehicle changes over time in a first period; acquiring correction data in which a speed-related parameter in the acquired first speed data changes over time and has a variation according to the speed; and acquiring second speed data in which the speed changes over time in a second period shorter than the first period by correcting the first speed data based on the correction data.

12. An information processing method executed in an information processing device, comprising: acquiring first speed data in which the speed of a vehicle changes over time in a first period; acquiring correction data in which a speed-related parameter in the acquired first speed data changes over time and has a variation according to the speed; and acquiring second speed data in which the speed changes over time in a second period shorter than the first period by correcting the first speed data based on the correction data.

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