Information processing device, information processing system, program, and information processing method
The information processing device estimates ambient tire temperature using traveling and weather data, and engine status to predict tire durability without additional sensors, addressing the cost issue of conventional methods by leveraging existing vehicle systems.
Patent Information
- Application Number
- PCT/JP2024/021216
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-07-20
- Filing Date
- 2024-06-11
- Publication Date
- 2025-01-23
AI Technical Summary
Conventional methods for predicting tire durability require additional attachments like temperature sensors and recording devices to vehicles, increasing costs.
An information processing device that estimates ambient tire temperature using traveling information, weather data, and engine operating status without additional sensors, by calculating relational expressions from past data to determine temperature changes and engine status.
Enables accurate prediction of tire durability at a lower cost without the need for additional hardware, considering the engine as a heat source and using existing vehicle configurations.
Smart Images

Figure JP2024021216_23012025_PF_FP_ABST
Abstract
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, there are known techniques for accurately acquiring the ambient temperature around a tire when predicting the durability state of a tire mounted on a vehicle. For example, there is known a technique for measuring and recording the ambient temperature around the tire by additionally attaching a temperature sensor and a recording device to the vehicle. For example, Patent Document 1 discloses a device for estimating the wear state of a tire mounted on a vehicle. The device has a temperature sensor that acquires the temperature outside the vehicle.
[0003] Japanese Patent Application Laid-Open No. 2022-160933
[0004] However, in the conventional technology in which a temperature sensor and a recording device are additionally attached to a vehicle, the cost of continuously predicting the durability state of a tire increases.
[0005] The present disclosure provides a technology that can contribute to obtaining information necessary for predicting the durability state of a tire at low cost.
[0006] An information processing device according to one embodiment of the present disclosure includes: (1) a control unit that acquires driving information including a driving time and a driving position from a vehicle, acquires weather information for the vicinity of the driving position at the driving time based on the acquired driving information, and estimates the outside air temperature at the driving position at the driving time based on the acquired driving information and weather information.
[0007] (2) In the information processing device described in (1) above, the control unit may execute a process of estimating an ambient temperature of a tire of the vehicle based on the estimated outside air temperature and an operating status of an engine of the vehicle.
[0008] (3) In the information processing device according to (2), the control unit may determine the operating status based on a change over time in the traveling position in the process.
[0009] (4) In the information processing device described in (3) above, the control unit may determine whether the engine is on or off by determining whether the vehicle has been stopped for a period of time exceeding a threshold.
[0010] (5) In the information processing device according to any one of (2) to (4), the control unit may calculate, in the process, an elapsed time since the engine was turned on from an off state.
[0011] (6) In the information processing device according to (5), in the process, the control unit may obtain a first relational expression indicating a relationship between the increase in the ambient temperature and the elapsed time from past running data.
[0012] (7) In the information processing device described in any one of (2) to (6) above, the control unit may, in the processing, calculate a second relational expression from past data in which the outside air temperature and the ambient temperature are correlated with each other, and calculate the maximum temperature of the ambient temperature corresponding to the estimated outside air temperature based on the second relational expression.
[0013] (8) In the information processing device described in (7) above, the control unit may calculate the second relational expression using an approximation line for a maximum temperature among a plurality of the ambient temperatures obtained for each of a plurality of the outside air temperatures in the past data.
[0014] (9) In the information processing device according to any one of (2) to (8) above, the control unit may execute the processing using a different algorithm for each mounting position of the tire on the vehicle.
[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 a vehicle that provides the driving information to the information processing device.
[0016] A program according to an embodiment of the present disclosure (11) causes an information processing device to perform operations including: acquiring driving information from a vehicle, including a driving time and a driving position; acquiring weather information around the driving position at the driving time based on the acquired driving information; and estimating the outside air temperature at the driving position at the driving time based on the acquired driving information and weather information.
[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, including: acquiring driving information including a driving time and a driving position from a vehicle; acquiring weather information around the driving position at the driving time based on the acquired driving information; and estimating an outside air temperature at the driving position at the driving time based on the acquired driving information and weather information.
[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 contribute to obtaining information necessary for predicting the durability state of a tire at low cost.
[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 a third example of an information processing method executed by the information processing device of FIG. 1. FIG. 5 is a flowchart for explaining a fourth example of an information processing method executed by the information processing device of FIG. 1. FIG. 6 is a first diagram for explaining an example of processing executed by the information processing device of FIG. 1. FIG. 7 is a second diagram for explaining an example of processing 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] As an overview of one embodiment, the information processing device 10 acquires driving information from the vehicle 20, including the driving time and driving position of the vehicle 20. In the present disclosure, "driving information" includes, for example, the real-time driving time and driving position when an ambient temperature estimation process (described below) is performed on the vehicle 20 whose tire durability state is to be predicted. The information processing device 10 acquires meteorological information about the area around the driving position of the vehicle 20 at the driving time based on the acquired driving information. In the present disclosure, "weather information" includes information such as temperature acquired from a local weather observation system or the like.
[0026] The information processing device 10 estimates the outside air temperature at the driving position at the time of driving based on the acquired driving information and weather information. In the present disclosure, "outside air temperature" refers to, for example, the temperature of the atmosphere surrounding the vehicle, including the vehicle 20. The information processing device 10 executes a process to estimate the ambient temperature of the tires of the vehicle 20 based on the estimated outside air temperature and the operating status of the engine of the vehicle 20. In the present disclosure, "engine operating status" includes, for example, the elapsed time since the engine was turned on from off. "Atmospheric temperature" includes, for example, the temperature around the tires, which may affect the durability state of the tires. The ambient temperature is a temperature parameter required to predict the durability state of the tires of the vehicle 20.
[0027] 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.
[0028] As shown in FIG. 2, the information processing device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.
[0029] 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.
[0030] 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.
[0031] 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).
[0032] 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.
[0033] 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.
[0034] 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.
[0035] 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.
[0036] 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.
[0037] 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.
[0038] 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.
[0039] 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.
[0040] In step S101, the control unit 13 of the information processing device 10 acquires driving information including a driving time and a driving position from the vehicle 20. For example, the control unit 24 of the vehicle 20 acquires the driving position of the vehicle 20 as position information using the acquisition unit 23. The control unit 24 of the vehicle 20 associates the driving position acquired using the acquisition unit 23 with the driving time at that time, and generates driving information. 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.
[0041] In step S102, the control unit 13 of the information processing device 10 acquires, based on the travel information acquired in step S101, weather information about the vicinity of the travel position of the vehicle 20 at the travel time included in the travel information. For example, the control unit 13 of the information processing device 10 receives weather information generated by a regional weather observation system or the like from the regional weather observation system via the network 30 and the communication unit 11. Alternatively, the control unit 13 of the information processing device 10 receives, from the vehicle 20, weather information generated by a regional weather observation system or the like and once acquired by the vehicle 20 via the network 30 and the communication unit 11.
[0042] In step S103, the control unit 13 of the information processing device 10 estimates the outside air temperature at the traveling position of the vehicle 20 at the traveling time included in the traveling information, based on the traveling information acquired in step S101 and the weather information acquired in step S102. At this time, the control unit 13 may perform a complementation process to obtain an estimated value of the outside air temperature.
[0043] For example, when there is a time period in which information is missing from the weather information acquired in step S102, the control unit 13 may perform linear interpolation processing to connect sampling points of information located at both ends of the time period. When the driving time included in the driving information acquired in step S101 falls within the time period, the control unit 13 may estimate the outside air temperature using the weather information interpolated by the linear interpolation processing.
[0044] For example, when there is a spatial region where information is missing in the weather information acquired in step S102, the control unit 13 may perform linear interpolation processing to connect sampling points of information located at both ends of the spatial region. When the traveling position included in the traveling information acquired in step S101 is included in the spatial region, the control unit 13 may estimate the outside air temperature using the weather information interpolated by the linear interpolation processing.
[0045] 4 is a flowchart illustrating 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 described with reference to FIG. 4. The flowchart shown in FIG. 4 shows the flow of processing for calculating a first relational expression required for estimating the ambient temperature of the tires of the vehicle 20, which will be described later with reference to FIG. 6. The calculation of the first relational expression is performed based on past driving data when a vehicle identical to or different from the vehicle 20 is used as a test vehicle. The test vehicle is equipped with a temperature sensor capable of directly measuring the outside air temperature, the ambient temperature, and the like.
[0046] In step S201, the control unit 13 of the information processing device 10 acquires driving data of the test vehicle that has been driven normally. In the present disclosure, "driving data" includes the elapsed time since the test vehicle's engine was turned on, the ambient temperature of the test vehicle's tires measured directly by a temperature sensor, and the relationship between these parameters when the ambient temperature increases with increasing elapsed time. The control unit 13 receives driving data from the test vehicle via the network 30 and the communication unit 11, for example, the driving data generated by the test vehicle itself based on measurements made on the test vehicle. The control unit 13 stores the acquired driving data in the memory unit 12.
[0047] In step S202, the control unit 13 of the information processing device 10 acquires, from the past driving data acquired in step S201, the elapsed time since the engine of the measurement vehicle was turned on from off.
[0048] In step S203, the control unit 13 of the information processing device 10 acquires the ambient temperature of the tires of the measurement vehicle, which is directly measured by the temperature sensor, from the past driving data acquired in step S201.
[0049] In step S204, the control unit 13 of the information processing device 10 calculates a first relational expression that indicates the relationship between the increase in ambient temperature and elapsed time, based on the past driving data acquired in step S201. For example, the control unit 13 calculates the first relational expression based on the unsteady heat conduction equation while calculating necessary coefficients from the past driving data acquired in step S201. The control unit 13 stores the calculated first relational expression in the storage unit 12 as information.
[0050] 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 shows the flow of processing for calculating a second relational expression required for estimating the ambient temperature of the tires of the vehicle 20, which will be described later with reference to Fig. 6. The calculation of the second relational expression is performed based on past data acquired using a measurement vehicle, similar to the calculation of the first relational expression.
[0051] In step S301, the control unit 13 of the information processing device 10 acquires the outside air temperature, which is the temperature of the air surrounding the test vehicle, measured by a temperature sensor in the test vehicle while the test vehicle is running normally. For example, the control unit 13 receives the outside air temperature measured in the test vehicle from the test vehicle via the network 30 and the communication unit 11. The control unit 13 stores the acquired outside air temperature in the memory unit 12. In step S301, the control unit 13 may acquire outside air temperatures over a wide period from summer to winter in order to widen the range of values of the outside air temperature.
[0052] In step S302, the control unit 13 of the information processing device 10 acquires the ambient temperature of the tires of the test vehicle measured by a temperature sensor of the test vehicle running normally. For example, the control unit 13 receives the ambient temperature measured in the test vehicle from the test vehicle via the network 30 and the communication unit 11. The control unit 13 stores the acquired ambient temperature in the memory unit 12. In step S302, the control unit 13 acquires the ambient temperature corresponding to the outside air temperature acquired in step S301.
[0053] In step S303, the control unit 13 of the information processing device 10 generates data in which the outside air temperature acquired in step S301 and the ambient temperature acquired in step S302 are associated with each other, and stores the data in the storage unit 12.
[0054] In step S304, the control unit 13 of the information processing device 10 calculates a second relational expression from the past data stored in the storage unit 12 in step S303. For example, the control unit 13 calculates the second relational expression using an approximation line for the highest temperature among multiple ambient temperatures obtained for each of multiple outside air temperatures in the past data stored in the storage unit 12 in step S303. The control unit 13 stores the calculated second relational expression as information in the storage unit 12. As described above, the control unit 13 obtains the second relational expression that expresses the relationship between the outside air temperature and the ambient temperature.
[0055] FIG. 6 is a flowchart illustrating a fourth example of an information processing method executed by the information processing device 10 of FIG. 1 . The fourth example of the information processing method executed by the information processing device 10 of FIG. 1 will be mainly described with reference to FIG. 6 . The flowchart shown in FIG. 6 shows the flow of a process for estimating the ambient temperature of the tires of the vehicle 20. The control unit 13 of the information processing device 10 executes a process for estimating the ambient temperature of the tires of the vehicle 20 based on the outside air temperature estimated in step S103 of FIG. 3 and the operating status of the engine of the vehicle 20. As described below, in this process, the control unit 13 of the information processing device 10 determines the operating status of the engine of the vehicle 20 based on a change over time in the traveling position of the vehicle 20.
[0056] In step S401, the control unit 13 of the information processing device 10 estimates the outside air temperature at the traveling position of the vehicle 20 at the traveling time included in the traveling information acquired in step S101, according to the flowchart shown in FIG.
[0057] In step S402, the control unit 13 of the information processing device 10 determines whether the stop time of the vehicle 20 exceeds a threshold. The control unit 13 determines whether the vehicle 20 is moving or stopped based on, for example, a change in the running position over time included in the running information acquired in step S101 of the flowchart shown in Fig. 3. The control unit 13 determines that the vehicle 20 is stopped when the running position remains constant over time, and calculates the stop time, thereby performing a process of comparing the stop time of the vehicle 20 with a threshold.
[0058] If the control unit 13 of the information processing device 10 determines in step S402 that the stop time exceeds the threshold, it executes processing in step S403. If the control unit 13 of the information processing device 10 determines in step S402 that the stop time does not exceed the threshold, i.e., that the stop time is equal to or less than the threshold, it executes processing in step S404. By determining in step S402 whether the stop time of the vehicle 20 exceeds the threshold, the control unit 13 determines whether the engine of the vehicle 20 is on or off in steps S404 and S403, respectively.
[0059] In step S403, if the control unit 13 of the information processing device 10 determines that the stopping time of the vehicle 20 exceeds the threshold value in step S402, it determines that the engine of the vehicle 20 is off.
[0060] In step S404, if the control unit 13 of the information processing device 10 determines in step S402 that the stopping time of the vehicle 20 does not exceed the threshold, it determines that the engine of the vehicle 20 is on.
[0061] In step S405, the control unit 13 of the information processing device 10 calculates the elapsed time since the engine of the vehicle 20 was turned on from off, based on the determination process and discrimination process in steps S402 to S404.
[0062] In step S406, the control unit 13 of the information processing device 10 reads out the first relational expression calculated according to the flowchart shown in Fig. 4 from the storage unit 12. As a result, the control unit 13 acquires the first relational expression indicating the relationship between the increase in ambient temperature and the elapsed time from past driving data.
[0063] In step S407, the control unit 13 of the information processing device 10 reads out the second relational expression calculated according to the flowchart shown in Fig. 5 from the storage unit 12. As a result, the control unit 13 acquires the second relational expression from past data in which the outside air temperature and the ambient temperature are associated with each other.
[0064] In step S408, the control unit 13 of the information processing device 10 calculates the maximum ambient temperature corresponding to the ambient temperature around the vehicle 20 estimated in step S401, based on the second relational expression acquired in step S407. In the present disclosure, the "maximum ambient temperature" includes, for example, an ambient temperature located on an approximation line for the maximum ambient temperature among multiple ambient temperatures obtained for each of multiple ambient temperatures in past data. In step S408, the control unit 13 calculates the maximum ambient temperature at the traveling time when the ambient temperature was estimated in step S401.
[0065] In step S409, the control unit 13 of the information processing device 10 calculates the current ambient temperature based on the elapsed time calculated in step S405, the maximum reachable temperature calculated in step S408, and the first relational expression acquired in step S406, which indicates the rising relationship of the ambient temperature. For example, the control unit 13 assumes that the ambient temperature, which was approximately the same as the estimated outside air temperature immediately after the engine was turned on, will eventually reach the maximum reachable temperature, and links these two temperatures with the first relational expression having a predetermined time constant. The control unit 13 calculates the current ambient temperature, which is higher than the estimated outside air temperature, by correcting the outside air temperature estimated in step S401 using the first relational expression based on the unsteady heat conduction equation.
[0066] The control unit 13 of the information processing device 10 estimates the ambient temperature of the tires of the vehicle 20 in the above-described manner.
[0067] FIG. 7 is a first diagram illustrating an example of processing executed by the information processing device 10 of FIG. 1 . FIG. 7 is a graph showing past data stored in the memory unit 12 in step S303 of the flowchart of FIG. 5 . In the past data, the outside air temperature and the ambient temperature are associated with each other. The horizontal axis of the graph in FIG. 7 represents the outside air temperature, which is the temperature of the air surrounding the test vehicle, measured by a temperature sensor on the test vehicle. The vertical axis of the graph in FIG. 7 represents the ambient temperature of the test vehicle's tires, measured by a temperature sensor on the test vehicle.
[0068] Basically, the continuous operation of the engine of the test vehicle generates heat, which increases the ambient temperature of the test vehicle's tires located close to the engine. As a result, as shown in the graph of Figure 7, almost all of the ambient temperature values are higher than the corresponding ambient air temperature. 1 <T 2 <T 3 <T 4 <T 5 is.
[0069] The control unit 13 calculates the second relational expression using an approximation line for the maximum temperature among a plurality of ambient temperatures obtained for each of a plurality of outside air temperatures in such past data. As an example, the control unit 13 calculates the second relational expression using a linear approximation line, as shown by the dashed straight line in Figure 7.
[0070] Fig. 8 is a second diagram illustrating an example of processing executed by the information processing device 10 of Fig. 1. Fig. 8 is a graph comparing the ambient temperature estimated by the information processing device 10 with the actual measured value of the ambient temperature directly obtained using a temperature sensor or the like. In Fig. 8, the solid line indicates the ambient temperature estimated by the information processing device 10. The dashed line indicates the actual measured value of the ambient temperature directly obtained using a temperature sensor or the like. The dotted line indicates the outside air temperature estimated by the information processing device 10 based on weather information.
[0071] In Figure 8, the engine switches from on to off at the boundary of the two-dot chain line I. The engine switches from off to on at the boundary of the two-dot chain line II. The engine is off during the time period from the two-dot chain line I to the two-dot chain line II. The engine is on during other time periods.
[0072] At the time when the engine switches from on to off in the dashed-two-dot line II, the ambient temperature shown by the solid line is approximately the same as the outside air temperature shown by the dotted line. During the following time period, the ambient temperature shown by the solid line tends to rise, diverging from the outside air temperature shown by the dotted line toward the higher side. During this time period, the ambient temperature shown by the solid line tends to rise depending on the time elapsed since the engine switched from off to on. During this time period, the profile of the time change in the ambient temperature shown by the solid line closely matches the profile of the time change in the actual measured ambient temperature shown by the dashed line. Therefore, the tire ambient temperature estimation process executed by the information processing device 10 in FIG. 1 functions with high accuracy.
[0073] According to the embodiment described above, it is possible to acquire information necessary for predicting the durability state of tires at low cost. For example, the information processing device 10 estimates the outside air temperature at the driving position of the vehicle 20 at the time of driving based on the acquired driving information and weather information. This allows the information processing device 10 to acquire the outside air temperature at the driving position of the vehicle 20 without additionally attaching a temperature sensor, a recording device, or the like to the vehicle 20. The vehicle 20 only needs to have the original components necessary for driving, and does not need to additionally include a temperature sensor, a recording device, or the like. Therefore, the cost of operating the vehicle 20 to predict the durability state of tires is reduced.
[0074] The information processing device 10 executes a process for estimating the ambient temperature of the tires of the vehicle 20 based on the estimated outside air temperature and the operating status of the engine of the vehicle 20. As a result, the information processing device 10 can acquire the ambient temperature of the tires at the traveling position of the vehicle 20 at the time of traveling, without additionally attaching a temperature sensor, a recording device, etc. to the vehicle 20. The vehicle 20 only needs to have the original components necessary for traveling, and does not need to have additional temperature sensors, recording devices, etc. Therefore, the cost of the vehicle 20 when acquiring the ambient temperature of the tires as a parameter for predicting the durability state of the tires is reduced.
[0075] In addition, the information processing device 10 executes a process for estimating the ambient temperature of the tires of the vehicle 20 based on the operating status of the engine of the vehicle 20, thereby making it possible to incorporate the influence of the engine as a heat source into the estimation of the ambient temperature. The information processing device 10 can more accurately estimate the ambient temperature of the tires of the vehicle 20 while incorporating the influence of the engine as a heat source. As a result, the information processing device 10 can more accurately predict the durability state of the tires.
[0076] In the ambient temperature estimation process, the information processing device 10 determines the engine operating status based on changes over time in the traveling position of the vehicle 20. This allows the information processing device 10 to acquire the engine operating status of the vehicle 20 without additionally attaching a sensor or the like to the vehicle 20 for acquiring information about the engine operating status. The vehicle 20 only needs to have the original components necessary for traveling, and does not need to have additional sensors or the like for acquiring information about the engine operating status. This reduces the cost of the vehicle 20 in the ambient temperature estimation process for predicting the durability state of the tires.
[0077] The information processing device 10 determines whether the engine of the vehicle 20 is on or off by determining whether the stoppage time of the vehicle 20 exceeds a threshold. As a result, the information processing device 10 can accurately determine whether the engine of the vehicle 20 is on or off based on the position information acquired by the acquisition unit 23 of the vehicle 20. The information processing device 10 can acquire information on whether the engine of the vehicle 20 is on or off without additionally attaching a sensor or the like to the vehicle 20 for acquiring information on whether the engine is on or off. The vehicle 20 only needs to have the original configuration necessary for traveling, and does not need to have an additional sensor or the like for acquiring information on whether the engine is on or off. Therefore, the cost of the vehicle 20 in the ambient temperature estimation process for predicting the durability state of the tires is reduced.
[0078] In the ambient temperature estimation process, the information processing device 10 calculates the elapsed time since the engine of the vehicle 20 was turned on from off. This enables the information processing device 10 to more accurately execute the tire ambient temperature estimation process required to predict the tire durability state. The information processing device 10 executes the process of estimating the tire ambient temperature of the vehicle 20 based on the calculated elapsed time, thereby enabling the estimation of the ambient temperature to take into account the influence of the elapsed time. The information processing device 10 can more accurately estimate the tire ambient temperature of the vehicle 20 while taking into account the influence of the elapsed time. As a result, the information processing device 10 can more accurately predict the tire durability state.
[0079] In the ambient temperature estimation process, the information processing device 10 acquires a first relational expression that indicates the relationship between the increase in ambient temperature and elapsed time from past driving data. This enables the information processing device 10 to more accurately execute the tire ambient temperature estimation process required to predict the tire durability state. The information processing device 10 can also estimate the ambient temperature of the tires of the vehicle 20 more accurately in accordance with the acquired first relational expression. As a result, the information processing device 10 can more accurately predict the tire durability state.
[0080] In the ambient temperature estimation process, the information processing device 10 calculates a second relational expression from past data in which the outside air temperature and the ambient temperature are correlated with each other, and calculates the maximum ambient temperature corresponding to the estimated outside air temperature based on the second relational expression. This allows the information processing device 10 to more accurately estimate the ambient temperature of the tire, which is necessary for predicting the durability state of the tire. The information processing device 10 also estimates the ambient temperature of the tire of the vehicle 20 based on the calculated maximum temperature, thereby incorporating the influence of the maximum temperature when estimating the ambient temperature. For example, if the ambient temperature calculated based on the first relational expression exceeds the maximum temperature calculated based on the second relational expression, the information processing device 10 can determine the maximum temperature as the ambient temperature. The information processing device 10 can more accurately estimate the ambient temperature of the tire of the vehicle 20 while incorporating the influence of the maximum temperature. As a result, the information processing device 10 can more accurately predict the durability state of the tire.
[0081] The information processing device 10 calculates the second relational expression using an approximation line for the maximum temperature among multiple ambient temperatures obtained for each of multiple outside air temperatures in past data. This allows the information processing device 10 to more accurately calculate the maximum ambient temperature. The information processing device 10 can use a more accurate maximum ambient temperature in the tire ambient temperature estimation process required to predict the tire durability state, and as a result, can estimate the ambient temperature with more accuracy. As a result, the information processing device 10 can more accurately predict the tire durability state.
[0082] 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.
[0083] 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.
[0084] 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.
[0085] 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.
[0086] 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.
[0087] In addition to the various processes described in the above embodiment, the information processing device 10 may execute the ambient temperature estimation process using a different algorithm for each tire mounting position on the vehicle 20. For example, the information processing device 10 may acquire information on the tire mounting position on the vehicle 20 and estimate the ambient temperature using a different algorithm for each tire on the vehicle 20 based on the information. The algorithm may include a method for calculating a first relational expression that indicates the relationship of the increase in ambient temperature with respect to elapsed time, and a method for calculating the maximum ambient temperature based on a second relational expression. As described above, the information processing device 10 can estimate the ambient temperature for each tire on the vehicle 20 with higher accuracy.
[0088] In the above embodiment, the information processing device 10 executes the process of estimating the ambient temperature of the tires of the vehicle 20 based on the estimated outside air temperature and the operating status of the engine of the vehicle 20. However, the present invention is not limited to this. The information processing device 10 may execute the process of estimating the ambient temperature of the tires of the vehicle 20 using any other method based on the estimated outside air temperature.
[0089] In the above embodiment, the information processing device 10 has been described as determining the operating status of the engine of the vehicle 20 based on the change over time in the traveling position of the vehicle 20 in the ambient temperature estimation process, but the present invention is not limited to this. The information processing device 10 may determine the operating status of the engine by directly acquiring information on the operating status of the engine acquired by a sensor or the like in the vehicle 20.
[0090] In the above embodiment, the information processing device 10 determines whether the engine is on or off by determining whether the vehicle 20 has been stopped for a period of time exceeding a threshold value, but the present invention is not limited to this. The information processing device 10 may determine whether the engine is on or off by directly acquiring information indicating whether the engine is on or off obtained by a sensor or the like in the vehicle 20.
[0091] In the above embodiment, the information processing device 10 calculates the elapsed time since the engine of the vehicle 20 was turned on from off in the ambient temperature estimation process, but the present invention is not limited to this. The information processing device 10 does not have to perform such a calculation process.
[0092] In the above embodiment, the information processing device 10 is described as acquiring a first relational expression indicating the relationship between the increase in ambient temperature and elapsed time from past driving data in the ambient temperature estimation process. However, this is not limited to this. The information processing device 10 may acquire a machine learning model based on past driving data that correlates elapsed time with the ambient temperature, and use the machine learning model to acquire the relationship between the increase in ambient temperature and elapsed time. The machine learning model may include, for example, a model constructed by multiple regression analysis using the ambient temperature in the driving data as the objective variable and the elapsed time in the driving data as the explanatory variable. Alternatively, the machine learning model may include a model constructed using another method, such as a neural network.
[0093] In the above embodiment, the information processing device 10, in the ambient temperature estimation process, calculates a second relational expression from past data in which the outside air temperature and the ambient temperature are correlated with each other, and calculates the maximum ambient temperature corresponding to the estimated outside air temperature based on the second relational expression. However, this is not limited to this. The information processing device 10 may acquire a machine learning model based on past data in which the outside air temperature and the ambient temperature are correlated with each other, and acquire the maximum ambient temperature corresponding to the outside air temperature using the machine learning model. The machine learning model may include, for example, a model constructed by multiple regression analysis using the maximum ambient temperature in the past data as the dependent variable and the outside air temperature in the past data as the explanatory variable. Alternatively, the machine learning model may include a model constructed using other methods, such as a neural network.
[0094] The information processing device 10 may acquire a machine learning model based on past data that correlates the outside air temperature, elapsed time, and ambient temperature, and may use the machine learning model to directly acquire the ambient temperature relative to the outside air temperature and elapsed time. The machine learning model may include, for example, a model constructed by multiple regression analysis using the ambient temperature in the past data as the dependent variable and the outside air temperature and elapsed time in the past data as the explanatory variables. Alternatively, the machine learning model may include a model constructed using other methods, such as a neural network.
[0095] In the above embodiment, the information processing device 10 calculates the second relational expression using an approximation line for the maximum temperature among the plurality of ambient temperatures obtained for each of the plurality of outside air temperatures in the past data. However, this is not limited to this. The information processing device 10 may calculate the second relational expression based on any temperature other than the maximum temperature. For example, the information processing device 10 may calculate the second relational expression using an approximation line for the average value of the plurality of ambient temperatures obtained for each of the plurality of outside air temperatures in the past data.
[0096] In the above embodiment, the information processing device 10 calculates the second relational expression using a linear approximation line as shown by the dashed straight line in Fig. 7, but is not limited to this. The information processing device 10 may calculate the second relational expression using a non-linear approximation line.
[0097] 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 server via the network 30 and the communication unit 11.
[0098] In the above embodiment, when there is a time period in which information is missing from the acquired weather information, the information processing device 10 performs linear interpolation processing to connect the sampling points of information located at both ends of the time period, but this is not limiting. The information processing device 10 may also perform non-linear interpolation processing.
[0099] In the above embodiment, when there is a spatial region where information is missing in the acquired weather information, the information processing device 10 performs linear interpolation processing to connect the sampling points of information located at both ends of the spatial region. However, the present invention is not limited to this. The information processing device 10 may also perform non-linear interpolation processing.
[0100] 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 contribute to obtaining information necessary for predicting the durability state of a tire at low cost.
[0101] 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 driving information including a driving time and a driving position from a vehicle, acquires weather information for the vicinity of the driving position at the driving time based on the acquired driving information, and estimates the outside air temperature at the driving position at the driving time based on the acquired driving information and weather information.
2. An information processing device according to claim 1, wherein the control unit executes a process of estimating an ambient temperature of the vehicle's tires based on the estimated outside air temperature and an operating condition of the vehicle's engine.
3. An information processing device according to claim 2, wherein the control unit, in the process, determines the operating status based on a change over time in the running position.
4. An information processing device according to claim 3, wherein the front control unit determines whether the engine is on or off by determining whether the vehicle has been stopped for a period of time that exceeds a threshold value.
5. An information processing device according to any one of claims 2 to 4, wherein the control unit calculates, in the process, an elapsed time since the engine was turned on from an off state.
6. An information processing device according to claim 5, wherein the control unit, in the process, obtains a first relational expression that indicates a relationship of the increase in the ambient temperature with respect to the elapsed time from past driving data.
7. An information processing device according to any one of claims 2 to 4, wherein the control unit, in the processing, calculates a second relational equation from past data in which the outside air temperature and the ambient temperature are correlated with each other, and calculates the maximum attained temperature of the ambient temperature corresponding to the estimated outside air temperature based on the second relational equation.
8. An information processing device according to claim 7, wherein the control unit calculates the second relational expression using an approximation line for the maximum temperature among the plurality of ambient temperatures obtained for each of the plurality of outside air temperatures in the past data.
9. An information processing device according to any one of claims 2 to 4, wherein the control unit executes the processing using a different algorithm for each mounting position of the tire on the vehicle.
10. An information processing system comprising: an information processing device according to any one of claims 1 to 4; and a vehicle that provides the driving information to the information processing device.
11. A program that causes an information processing device to perform operations including: acquiring driving information from a vehicle, including a driving time and a driving position; acquiring weather information for the vicinity of the driving position at the driving time based on the acquired driving information; and estimating the outside air temperature at the driving position at the driving time based on the acquired driving information and weather information.
12. An information processing method executed in an information processing device, comprising: acquiring driving information from a vehicle, the driving information including a driving time and a driving position; acquiring weather information for the vicinity of the driving position at the driving time based on the acquired driving information; and estimating the outside air temperature at the driving position at the driving time based on the acquired driving information and weather information.
Citation Information
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